On relative errors of floating-point operations: optimal bounds and applications

Size: px
Start display at page:

Download "On relative errors of floating-point operations: optimal bounds and applications"

Transcription

1 On relative errors of floating-point operations: optimal bonds and applications Clade-Pierre Jeannerod, Siegfried M. Rmp To cite this version: Clade-Pierre Jeannerod, Siegfried M. Rmp. On relative errors of floating-point operations: optimal bonds and applications. Mathematics of Comptation, American Mathematical Society, 2018, 87, pp < /mcom/3234>. <hal v4> HAL Id: hal Sbmitted on 3 Nov 2016 HAL is a mlti-disciplinary open access archive for the deposit and dissemination of scientific research docments, whether they are pblished or not. The docments may come from teaching and research instittions in France or abroad, or from pblic or private research centers. L archive overte plridisciplinaire HAL, est destinée a dépôt et à la diffsion de docments scientifiqes de nivea recherche, pbliés o non, émanant des établissements d enseignement et de recherche français o étrangers, des laboratoires pblics o privés.

2 ON RELATIVE ERRORS OF FLOATING-POINT OPERATIONS: OPTIMAL BOUNDS AND APPLICATIONS CLAUDE-PIERRE JEANNEROD AND SIEGFRIED M. RUMP Abstract. Ronding error analyses of nmerical algorithms are most often carried ot via repeated applications of the so-called standard models of floating-point arithmetic. Given a rond-to-nearest fnction fl and barring nderflow and overflow, sch models bond the relative errors E 1 (t) = t fl(t) / t and E 2 (t) = t fl(t) / fl(t) by the nit rondoff. This paper investigates the possibility and the seflness of refining these bonds, both in the case of an arbitrary real t and in the case where t is the exact reslt of an arithmetic operation on some floating-point nmbers. We show that E 1 (t) and E 2 (t) are optimally bonded by /(1 + ) and, respectively, when t is real or, nder mild assmptions on the base and the precision, when t = x ± y or t = xy with x, y two floating-point nmbers. We prove that while this remains tre for division in base β > 2, smaller, attainable bonds can be derived for both division in base β = 2 and sqare root. This set of optimal bonds is then applied to the ronding error analysis of varios nmerical algorithms: in all cases, we obtain significantly shorter proofs of the best-known error bonds for sch algorithms, and/or improvements on these bonds themselves. 1. Introdction Given two integers β, p 2, let F be the associated set of floating-point nmbers having base β, precision p, and no restriction on the exponent range: F = {0} {M β e : M, e Z, β p 1 M < β p }. Let also fl : R F denote any rond-to-nearest fnction, sch that (1.1) t fl(t) = min t f, t R. f F In particlar, no specific tie-breaking strategy is assmed for the fnction fl. Two relative errors can then be defined, depending on whether the exact vale or the ronded vale is sed to divide the absolte error in (1.1): the error relative to t is E 1 (t) = while the error relative to fl(t) is E 2 (t) = t fl(t) t t fl(t) fl(t) if t 0, if fl(t) 0. (In each case the relative error may be defined to be zero if the denominator is zero: the exponent range being nbonded, fl(t) = 0 implies t = 0, so in both cases a zero denominator means that no error occrs when ronding t.) November 3, Mathematics Sbject Classification. Primary 65G50. 1

3 2 C.-P. JEANNEROD AND S. M. RUMP For ronding error analysis prposes, the most commonly sed bonds are E 1 (t) and E 2 (t), where = 1 2 β1 p is the nit rondoff associated with fl and F, and sch bonds are typically handled via the so-called standard models fl(t) = t(1 + δ 1 ) = t/(1 + δ 2 ), δ 1, δ 2 ; see [5, pp ]. It is also known that the bond on the first relative error can be refined slightly [12, p. 232], 1 so that (1.2) E 1 (t) and E 2 (t). 1 + These worst-case bonds hold for any real nmber t and any ronding fnction fl. Frthermore, they can be regarded as optimal in the sense that each of them is attained for some pair (t, fl) with t expressed in terms of β and p: since 1 + is exactly halfway between the two consective elements 1 and of F, we have E 1 (1 + ) = /(1 + ) and, assming frther that fl ronds ties to even, E 2 (1 + ) =. In this paper, we investigate the possibility and the seflness of refining the bonds in (1.2) when t is not jst an arbitrary real nmber bt the exact reslt of an operation on some floating-point nmber(s), that is, when t = x op y, x, y F, op {+,,, /} : F F R as well as t = x. Or first contribtion is to establish optimal bonds on both E 1 and E 2 for each of these five basic operations, as shown in Table 1. Table 1. Optimal relative error bonds for varios inpts t. t bond on E 1 (t) bond on E 2 (t) real nmber x ± y xy x/y { 2 2 if β = 2, { if β = 2, if β > 2 if β > 2 1+ x As we shall see later in the paper, each of these bonds is attained for some explicit inpt vales in F and ronding fnctions fl, possibly nder some mild (necessary and sfficient) conditions on β and p. Specifically, for addition, sbtraction, and mltiplication the condition for optimality is that β is even, and in the case of mltiplication in base 2 it is that 2 p + 1 is not a Fermat prime. In most practical sitations sch conditions are satisfied and ths the general bonds in (1.2) remain 1 The refined bond E1 (t) /(1 + ) already appears in [18, p. 74] and, in some special cases, in [2] for β = 2 and [6] for β even.

4 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 3 the best ones for floating-point addition, sbtraction, and mltiplication; as Table 1 shows, this is also the case of division in any base larger than 2. In contrast, for division in base 2 and for sqare root, the general bond /(1+) 2 on E 1 can be decreased frther to 2 2 and to 1 (1+2) 1/ , respectively; likewise, the general bond on E 2 can be decreased to ( 2 2 )/( ) 3 2 and (1 + 2) 1/ Or second contribtion is to show that in the context of ronding error analysis of nmerical algorithms, applying these optimal bonds in a systematic way leads to simpler and sharper bonds, and/or to more direct proofs of existing ones. In particlar, this allows s to establish the following three new error bonds: (1.3) (1.4) For the smmation of n floating-point nmbers x 1,..., x n (sing n 1 floating-point additions and any ordering), we show that the reslting floating-point approximation ŝ satisfies ŝ n n 1 x i e i (n 1) 1 + n x i, where e i denotes the absolte error of the ith floating-point addition. For the smmation of n real nmbers x 1,..., x n, we show that by first ronding each x i into fl(x i ) and then smming the fl(x i ) in any order, the reslting approximation ŝ satisfies ŝ n x i n n 1 n d i + e i ζ n x i, ζ n < n, where the d i are given by d i = x i fl(x i ) and the e i are as before. For the Eclidean norm of a vector of n floating-point nmbers x 1,..., x n we show that smming the sqares in any order and then taking the sqare root of the reslt yields a floating-point nmber r sch that ( n ) 1/2 (1.5) r = x 2 i (1 + ɛ), ɛ (n/2 + 1). Note that each of these bonds holds withot any restriction on n. The bonds in (1.3) and (1.4) improve pon the best previos ones, from [10], in two ways: they are sharper and apply not only to the absolte error of ŝ bt also to the sm of the absolte local errors. Frthermore, we will see that the new bond in (1.3) implies the one in (1.4) almost immediately; in other words, sing (1.3) allows s to recover the constant n established in [10, Proposition 4.1] for sms of n reals (and ths n-dimensional inner prodcts as well), bt in a mch more direct way. Finally, the bond in (1.5) nicely replaces the expression (n/2 + 1) + O( 2 ) that wold reslt from sing the sboptimal bond E 1 ( x). Besides the evalation of sms and norms, and to illstrate frther the benefits of applying the refined bonds in Table 1, we provide for other typical examples of ronding error analysis. These examples deal with small arithmetic expressions, minors of tridiagonal matrices, Cholesky factorization, and complex floating-point mltiplication. We shall see that in each case the existing error bond can be either replaced by a simpler and sharper one, or recovered via a significantly shorter proof. Notation and assmptions. All or reslts hold nder the cstomary assmption that β, p 2. Frthermore, following [5] (and nless stated otherwise) we

5 4 C.-P. JEANNEROD AND S. M. RUMP shall ignore nderflow and overflow by assming that the exponent range of F is nbonded. Finally, the common tool sed to establish all the error bonds in Table 1 is the fnction fp : R F 0 from [16], called nit in the first place (fp) and defined as follows: fp(0) = 0 and, if t R\{0}, fp(t) is the largest integer power of β sch that fp(t) t. Hence, in particlar, for t nonzero, (1.6a) and for any t, (1.6b) fp(t) t < βfp(t), fp(t) fl(t) βfp(t). Otline. This paper is organized as follows. We begin in Section 2 by recalling how to derive the bonds in (1.2) and by completely characterizing their attainability. Section 3 then gives proofs for all the bonds annonced in Table 1 together with explicit expressions of inpt vales at which these bonds are attained. A first application of these reslts is described in Section 4, where we establish the new bonds for smmation shown in (1.3) and (1.4). We conclde in Section 5 with the derivation of the bond (1.5) together with the analysis of for other examples. 2. Optimal error bonds when ronding a real nmber Using the fnction fp, the bonds E i (t) for i = 1, 2 are easily derived as follows. First, recall from (1.6) that t = 0 belongs to the right-open interval [fp(t), β fp(t)), which contains (β 1)β p 1 eqally-spaced elements of F. The distance between two sch consective elements is ths β fp(t) fp(t) (β 1)β = 2 fp(t), p 1 and ronding to nearest implies that the absolte error is bonded as (2.1) t fl(t) fp(t). This bond is sharp and the vales at which it is attained are the midpoints of F, that is, the rational nmbers lying exactly halfway between two consective elements of F. Dividing both sides of (2.1) by either t or fl(t) gives (2.2) E 1 (t) fp(t) t and E 2 (t) fp(t) fl(t), and by sing the lower bonds in (1.6) we arrive at the classical bonds E 1 (t) and E 2 (t). As noted in [5, Theorem 2.2], we have in fact the strict ineqality E 1 (t) <, since t cannot be at the same time a midpoint and eqal to its fp; on the other hand, the derivation above shows that the bond on E 2 (t) is attained if and only if t is a midpoint sch that fl(t) = fp(t). Let s now refine the bond E 1 (t) <. As shown in [12, p. 232], all we need for this is a lower bond on t slightly sharper than the one in (1.6): by definition of ronding to nearest, t fl(t) t f for all f F, so taking in particlar f = sign(t)fp(t) gives t fl(t) t fp(t); in other words, (2.3) fp(t) + t fl(t) t and, becase of (2.1), eqality occrs if and only if t (1 + )fp(t). Ths, by applying (2.3) and then (2.1) to the definition of E 1, we find that E 1 (t) t fl(t) fp(t) + t fl(t) 1 +.

6 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 5 Frthermore, de to the conditions of attainability of (2.1) and (2.3) given above, this bond on E 1 (t) is attained if and only if t is a midpoint sch that t (1 + )fp(t), that is, if and only if t = (1 + )fp(t). We smmarize or discssion in the theorem below. Althogh the bonds given there already appear in [18, p. 74] and [12, p. 232] for E 1, and in [5, Theorem 2.3] for E 2, the characterization of their attainability does not seem to have been reported elsewhere. Theorem 2.1. If t R\{0}, then E 1 (t) 1 + and E 2 (t). Frthermore, the bond on E 1 is attained if and only if t = (1 + )fp(t), and the bond on E 2 is attained if and only if t = (1 + )fp(t) and fl(t) = fp(t). 3. Optimal error bonds for floating-point operations We establish here optimal bonds on both E 1 and E 2 for the operations of addition, sbtraction, mltiplication, fsed mltiply-add, division, and sqare root Addition, sbtraction, and fsed mltiply-add. When t has the form t = x + y with x, y in F, we show in the theorem below that the general bonds E 1 (t) 1+ and E 2(t) given in (1.2) remain optimal nless the basis β is odd. This extends the analysis done by Holm [6], who considers only the first relative error and assmes implicitly that the basis is even. Theorem 3.1. Let β, p 2 and t = x + y with x, y F. The bonds in (1.2) are optimal if and only if β is even. Frthermore, when β is even, they are attained for (x, y) = (1, ) and ronding to nearest even. Proof. If β is odd, then = 1 2 β1 p = β 1 i=0 2 β i p with β 1 2 {1,..., β 1}, so and 1 + have infinite expansions in base β. Hence x + y cannot have the form ±(1 + )β e with e Z and ths, by Theorem 2.1, eqality never occrs in the bonds E 1 (x + y) /(1 + ) and E 2 (x + y). If β is even, then is in F. Conseqently, we can take (x, y) = (1, ), which gives E 1 (x + y) = /(1 + ) and, for ties ronded to even, E 2 (x + y) =. Since belongs to F for any β and since 1 + = (1 + 2) = 1 1 +, the theorem above extends immediately to sbtraction as well as to higher-level operations encompassing addition, like the fsed mltiply-add (x, y, z) fl(xy +z) Mltiplication. When t = xy with x, y F, the theorem below shows that the sitation is more sbtle than for addition: althogh the condition that β is even remains necessary for the optimality of the bonds E 1 (t) /(1 + ) and E 2 (t), it is sfficient only when β 2; when β = 2, optimality trns ot to be eqivalent to 2 p + 1 being composite. Theorem 3.2. Let β, p 2 and t = xy with x, y F. We then have the following, depending on the vale of the base β: If β = 2, then the bonds in (1.2) are optimal if and only if 2 p + 1 is not prime; frthermore, if D is a non-trivial divisor of 2 p +1, then these bonds are attained for ( ) (2 + 2)fp(D) D (x, y) =, D fp(d)

7 6 C.-P. JEANNEROD AND S. M. RUMP and ronding to nearest even. If β > 2, then the bonds in (1.2) are optimal if and only if β is even, and when the latter is tre these bonds are attained for and ronding to nearest even. (x, y) = (2 + 2, 2 1 ) Before proving this reslt, note that the attainability of the bond E 1 (xy) /(1 + ) has been observed in [6, p. 10] in the particlar case (β, p) = (2, 5), by taking x and y in the form shown above with D = 11. Proof. By Theorem 2.1, the optimality of the bonds in (1.2) when t = xy is eqivalent to the existence of a pair (x, y) F F sch that xy = (1 + )fp(xy). Assme first that β > 2. Similarly to Theorem 3.1, a necessary condition for optimality is that β be even. Frthermore, if β is even, then both and 2 1 are in F, and since their prodct eqals 1+, it sffices to take (x, y) = (2+2, 2 1 ) to show that the bonds in (1.2) are optimal. Let s now consider the case β = 2. Since fp(t 2 e ) = fp(t) 2 e for all (t, e) R Z, we can assme with no loss of generality that 1 x, y < 2. This implies that fp(xy) {1, 2} and, since x, y {1, 1 + 2, 1 + 4,...} and > 0, that the prodct xy cannot be eqal to 1 +. Hence, optimality is eqivalent to the existence of x, y F [1, 2) sch that xy = 2 + 2, that is, eqivalent to the existence of integers X, Y sch that (3.1) XY = (2 p + 1) 2 p 1 and 2 p 1 X, Y < 2 p. If 2 p + 1 is prime, then either X or Y mst be larger than 2 p, so (3.1) has no soltion. If 2 p +1 is composite, one can constrct a soltion (X 0, Y 0 ) to (3.1) as follows. Let D denote a non-trivial divisor of 2 p +1, and let X 0 = 2p +1 D fp(d) and Y 0 = D 2p 1 fp(d). Clearly, X 0 is an integer and the prodct X 0 Y 0 has the desired shape. Ths, it remains to check that Y 0 Z and that both X 0 and Y 0 are in the range [2 p 1, 2 p ). Since 2 p + 1 is odd, D mst be odd too, which implies that (3.2) fp(d) + 1 D < 2fp(D) and D < 2 p. Conseqently, fp(d) 2 p 1, so that fp(d) divides 2 p 1 and Y 0 is an integer. Frthermore, (3.2) leads to 2 p 1 < 2p +1 2 < X 0 (2 p + 1)(1 1 D ) < 2p and 2 p 1 < Y 0 < 2 p, so that X 0 and Y 0 satisfy the range constraint in (3.1). Finally, mltiplying X 0 and Y 0 by 2 = 2 1 p gives x 0 = (2 + 2)fp(D)/D and y 0 = D/fp(D) in F [1, 2) and sch that x 0 y 0 = = (1 + )fp(x 0 y 0 ). In the rest of this section, we show that the optimality condition 2 p + 1 is not prime arising in Theorem 3.2 for radix two is in fact satisfied in most practical sitations. First of all, if p is not a power of two, this condition is well known to hold [3, Exercise 18, 4], since p can be factored as p = mq with q odd and then (3.3) 2 p + 1 = (2 m + 1) ( 2 p m 2 p 2m + 2 m + 1 ). The binary basic formats specified by the IEEE standard being sch that p {24, 53, 113}, they fall into this category. More precisely, since here p is either odd or a mltiple of three, we dedce from (3.3) explicit divisors of 2 p + 1 and ths explicit pairs (x, y) F 2 for which the bonds in Theorem 3.2 are attained:

8 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 7 If p is odd, then 3 divides 2 p + 1 and we can take (x, y) = ( 4+4 3, 3 2) ; If p 0 mod 3, then 2 p + 1 can be factored as (2 p/3 + 1)(2 2p/3 2 p/3 + 1), so we can take (x, y) = (2 2 1/ /3, 1 + 1/3 ). In fact, the sfficient condition p is not a power of two is satisfied not only by those basic formats bt also by all the binary interchange formats of IEEE , for which either p {11, 24, 53, 113} or (3.4) p = k d + 13 with d = 4 log 2 k, k = 32j, j N 5, and where denotes ronding to a nearest integer. (A proof of the fact that (3.4) implies that p is not a power of two is deferred to Appendix A.) Assme now that p is a power of two. In this case 2 p + 1 is not prime if and only if it is not a prime nmber of the form F l = 2 2l + 1, called a Fermat prime. Crrently, the only known Fermat primes are F 0, F 1, F 2, F 3, F 4 and, on the other hand, F l is known to be composite for all 5 l 32; see for example [11, 17]. To smmarize, the only vales of p for which the optimality condition 2 p + 1 is not prime can fail to be satisfied are 2, 4, 8, 16 and p = 2 l , and none of these vales corresponds to an IEEE format Division. This section focses on the largest possible relative errors committed when ronding x/y with x, y nonzero elements of F. As the theorem below shows, the general bonds E 1 (t) 1+ and E 2(t) given in (1.2) can be refined frther for base 2, bt remain optimal for all other bases. Note that nlike for addition or mltiplication, optimality is achieved withot any extra assmption on the parity of β or the nmber theoretic properties of p. Theorem 3.3. Let β, p 2 and let x, y F be nonzero. Then { 2 2 if β = 2, E 1 (x/y) 1+ if β > 2, and { 2 2 E 2 (x/y) 1+ 2 if β = 2, 2 if β > 2. The bonds for β = 2 are attained at (x, y) = (1, 1 ) and, assming ties are ronded to even, the bonds for β > 2 are attained at (x, y) = (2 + 2, 2). Proof. When β > 2 the bonds are the general ones given in (1.2), and the fact they are attained for division follows immediately from F. The rest of the proof is ths devoted to the case β = 2. Let t = x/y. Since t cannot be a midpoint [13, 9], we have fl( t) = fl(t) and fl(t 2 e ) = fl(t) 2 e, e Z, regardless of the tie-breaking rle of fl. Conseqently, we can assme 1 t < 2 and x, y > 0. When t = 1 both E 1 and E 2 are zero, so we are left with handling t sch that 1 < t < 2. The lower bond on t implies x > y, which for x and y in F is eqivalent to x y + 2 fp(y). Hence, sing y (2 2)fp(y), (3.5) t fp(y) y = 1 1.

9 8 C.-P. JEANNEROD AND S. M. RUMP Since 1/(1 ) is strictly larger than the midpoint 1 +, it follows that (3.6) fl(t) {1 + 2, 1 + 4,...}. Assme for now that p 3. (For simplicity, the case β = p = 2 is handled separately at the end of the proof.) If fl(t) 1+4 then t 1+3, so that E 1 (t) fp(t)/t /(1+3) < 2 2 for p 3. Similarly, E 2 (t) /(1 + 4) < ( 2 2 )/( ) for p 3. If fl(t) = then, recalling (3.5) and the fact that t is not a midpoint, (3.7) 1 t < We now distingish between the following two sb-cases, depending on how t compares to fl(t) = 1 + 2: If t 1 + 2, then E 1 (t) = (1 + 2)/t 1 and E 2 (t) = 1 t/(1 + 2), so that the first ineqality in (3.7) gives immediately the desired bonds, which are attained only when t = 1/(1 ); since both 1 and 1 are in F when β = 2, this vale of t is obtained for (x, y) = (1, 1 ). If t > 1 + 2, then E 1 (t) = 1 (1 + 2)/t and E 2 (t) = t/(1 + 2) 1. The bond t < from (3.7) then gives immediately E 1 (t) < /(1 + 3), which is less than 2 2 for p 3. For E 2 (t), however, sing t < is not enogh and we show first how to replace this bond by the slightly sharper one (3.8) t = O( 3 ). The range of t implies y +2 fp(y) < x < y +6 fp(y). Note that y cannot be eqal to (2 2)fp(y), for otherwise 2fp(y) < x < (2+4)fp(y), ths contradicting the fact that x F. Therefore, y (2 4)fp(y) and x = y + 4 fp(y). Writing y = (1 + 2k)fp(y) with k a nonnegative integer, we dedce that t = k, so t < is eqivalent to k > 2 p 1 /3, that is, k (2 p 1 + 1)/3 for k is an integer. Hence 2k (1 + 2)/3 and (3.8) follows. Recalling that E 2 (t) = t/(1 + 2) 1 and applying (3.8), we arrive at E 2 (t) 2(1 ) (2+)(1+2), which is less than for p 3. 2 Assme now that p = 2. We have = 1/4 and, assming with no loss of generality that fp(x) = 1, we see that x {1, 3/2} and that y is either fp(y) or 3/2 fp(y). This yields for possibilities for t = x/y, all leading to E 1 (t) = E 2 (t) = 0 except for x = 1 and y = 3/2 fp(y). In this case, the constraint 1 < t < 2 implies frther y = 3/4 = 1. It follows that t = 1/(1 ), from which we dedce fl(t) = The annonced bonds ths hold also in the case β = p = 2, and since 1 and 1 are in F, they are attained for (x, y) = (1, 1 ).

10 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS Sqare root. Finally, we show how to refine frther the bonds E 1 (t) /(1 + ) and E 2 (t) in the special case where t = x for some positive floating-point nmber x, thereby establishing the optimal bonds in the last row of Table 1. This reslt is independent of any specific property of the base and the precision, and holds for any tie-breaking strategy. Theorem 3.4. Let β, p 2 and let x F be positive. Then E 1 ( 1 x) 1 and E 2 ( x) , and these bonds are attained only for x = (1 + 2)β 2e with e Z. Proof. Let t = x. Writing x = µβ 2e with e Z and µ F [1, β 2 ), we see that t = µ β e with µ {1, 1 + 2, 1 + 4,...}. If µ = 1 then E 1 (t) = E 2 (t) = 0, so we are left with the following two cases. If µ = then we dedce from 1 < < 1 + that fl(t) = β e and, conseqently, that E 1 (t) = 1 1/ and E 2 (t) = If µ then, recalling that µ < β 2, we have β e t < β e+1 and fp(t) = β e. This implies that E 1 (t) fp(t)/t / =: ϕ and it can be checked that ϕ < 1 1/ for 1/2. Frthermore, sing > 1 + gives fl(t) (1 + 2)β e and then E 2 (t) /(1 + 2) < Application to smmation 4.1. Sms of floating-point nmbers. Consider first the evalation of the sm of n floating-point nmbers. Here x 1,..., x n F are given and we assme that an approximation ŝ F to the exact sm s = x x n is prodced after n 1 floating-point additions, sing any evalation order. 2 Each of these additions takes a pair of floating-point nmbers, say (a, b) F 2, and retrns fl(a + b), ths committing the local error e := a + b fl(a + b). When evalating the sm as above, n 1 sch errors can occr and, denoting their set as {e 1,..., e n 1 }, it is easy to see that (4.1) s = e e n 1 + ŝ; see for example [5, p. 81]. The theorem below shows how to bond the sm of the e i and, therefore, ŝ s as well. This bond is slightly sharper than the one given in [10, Proposition 3.1] and can be established in the same way, sing /(1+) instead of to bond the relative ronding error committed by each floating-point addition. (For completeness a detailed proof is presented in Appendix B; note that as in [10] this bond holds even if nderflow occrs.) Theorem 4.1. For x 1,..., x n F, any order of evalation of the sm s = n x i prodces an approximation ŝ sch that the ronding errors e 1,..., e n 1 satisfy n 1 n ŝ s e i σ n 1 x i, σ n := n For example, for n = 4 possible evalation orders inclde ((x1 + x 2 ) + x 3 ) + x 4 and ((x 4 + x 3 ) + x 2 ) + x 1 and (x 1 + x 2 ) + (x 3 + x 4 ).

11 10 C.-P. JEANNEROD AND S. M. RUMP A direct conseqence of this reslt is a sharper and simpler bond for the following compensated smmation scheme (see [14] and the references therein): ŝ comp = fl(ŝ + ê), ê := a floating-point evalation of e e n 1. Since each e i belongs to F and can be compted exactly sing for example Knth s TwoSm algorithm [12, p. 236], we can apply Theorem 4.1 twice and, writing e = n 1 e i, we dedce that n (4.2) ê e σ n 1 σ n 2 x i. Since s = ŝ + e, we have also (4.3) ŝ comp s fl(ŝ + ê) (ŝ + ê) + ê e ŝ + ê + ê e 1 + ( 1 + s ) ê e. 1 + Then, combining (4.2) and (4.3) and sing the fact that ( )( 1+ ) we arrive at (4.4) ŝ comp s 1 + s + (n 1)(n 2) 2 n x i. The bond in (4.4) holds withot any restriction on n and regardless of the orderings sed for adding the x i and adding the e i. Frthermore, it is slightly sharper than the bond s + (n 1) 2 2 n (1 (n 1)) 2 x i given in [14, Proposition 4.5] in the special case of recrsive compensated smmation Sms of real nmbers. We now trn to the case where x 1,..., x n are in R instead of F. An approximation ŝ F to s = x x n R is obtained in two steps, by first ronding each x i into fl(x i ) and then evalating fl(x 1 ) + + fl(x n ) as above. A typical example is the comptation of inner prodcts, where each x i is the exact prodct of two given floating-point nmbers. Writing d i = x i fl(x i ) for the errors de to ronding the data and, as before, e i for the errors de to the n 1 additions, we dedce that the exact and compted sms are now related as (4.5) s = d d n + e e n 1 + ŝ. By combining (1.2) and Theorem 4.1 we obtain almost immediately the following bond on the sm of the d i and the e i. Theorem 4.2. For x 1,..., x n R, any order of evalation of the sm n fl(x i) prodces an approximation ŝ to the sm s = n x i sch that the ronding errors d 1,..., d n and e 1,..., e n 1 satisfy n n 1 n (1 + 2)n 2 ŝ s d i + e i ζ n x i, ζ n := (1 + ) 2 < n. Proof. The lower bond follows from (4.5). To establish the pper bond, let v = /(1 + ). Theorem 4.1 gives i<n e i (n 1)v i n fl(x i) and, on the other hand, (1.2) implies that d i v x i and fl(x i ) (1 + v) x i. Hence

12 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 11 i n d i + i<n e i (v + (n 1)v(1 + v)) i n x i, and it is easily checked that v +(n 1)v(1+v) simplifies to ((1+2)n 2 )/(1+) 2, which is less than n. Ths, the theorem above gives in particlar the bond n n ŝ x i ζn x i. This bond has a slightly smaller constant than the one given in [10, Proposition 4.1] and, perhaps more importantly, its proof is significantly shorter and avoids a tedios indction and fp-based case distinctions. Frthermore, the applications mentioned in [10] obviosly benefit directly from this new bond: for inner prodcts, matrix-vector prodcts, and matrix-matrix prodcts, the constants n obtained in [10, Theorem 4.2 and p. 343] can all be replaced by ζ n. 5. Other application examples 5.1. Example 1: Small arithmetic expressions. Ronding error analyses as those done in [5] typically involve bonds on θ n, where θ n is an expression of the form θ n = n (1 + δ i) 1 with δ i a relative error term associated with a single floating-point operation. Using the classical bond δ i it is easily checked that for all n, (5.1) n θ n (1 + ) n 1. Note that only the pper bond has the form n + O( 2 ), that is, contains terms nonlinear in. From (5.1) it follows that θ n (1 + ) n 1 and, assming n < 1, this bond itself is sally bonded above by the classical fraction γ n = n/(1 n). Using the refined bond E 1 (t) /(1 + ) from (1.2), we can replace δ i by δ i /(1 + ), which immediately leads to the refined enclosre (5.2) n 1 + θ n ( ) n 1. Althogh the pper bond in (5.2) still has O( 2 ) terms in general, it is bonded by n as long as n 3. Conseqently, by jst systematically sing E 1 (t) /(1 + ) instead of E 1 (t), we can replace γ n = n + O( 2 ) by n in every error analysis where θ n appears with n 3. For example, when evalating ab + cd in the sal way as r = fl(fl(ab) + fl(cd)), we have r = (ab(1 + δ 1 ) + cd(1 + δ 2 ))(1 + δ 3 ) with δ i /(1 + ). Hence r = ab(1 + θ 2 ) + cd(1 + θ 2), θ 2, θ 2 2, so the sal γ 2 is indeed replaced by 2. Note that once we have replaced E 1 (t) by E 1 (t) /(1+), we obtain that term 2 immediately, withot having to resort to a sophisticated fp-based argment as the one introdced in [1, pp ]. Similar examples inclde the evalation of small arithmetic expressions like the prodct x 1 x 2 x 3 x 4 (sing any parenthesization) or the sms ((x 1 +x 2 )+x 3 )+x 4 and ((x 1 +x 2 )+(x 3 +x 4 ))+((x 5 +x 6 )+(x 7 +x 8 )) (sing these specific parenthesizations); in each case the forward error bond classically involves γ 3, which we now replace by 3.

13 12 C.-P. JEANNEROD AND S. M. RUMP 5.2. Example 2: Leading principal minors of a tridiagonal matrix. Consider the tridiagonal matrix d 1 e 1 c 2 d 2 e 2 A = F n n, en 1 and let µ 1, µ 2,..., µ n be the seqence of its n leading principal minors. Writing µ 1 = 0 and µ 0 = 1, those minors are ths defined by the linear recrrence c n d n µ k = d k µ k 1 c k e k 1 µ k 2, 1 k n. Using the sal bond E 1 (t) and barring nderflow and overflow, Wilkinson shows in [19, 3] that the evalation of this recrrence prodces floating-point nmbers µ 1,..., µ n sch that µ k = d k (1 + ɛ k ) µ k 1 c k (1 + ɛ k)e k 1 (1 + ɛ k) µ k 2, where (1 ) 2 1 ɛ k (1 + ) 2 1 and (1 ) 3/2 1 ɛ k, ɛ k (1 + )3/2 1. In other words, the compted µ k are the leading principal minors of a nearby tridiagonal matrix A + A = [a ij (1 + δ ij )] that satisfies (5.3) 2 < δ ii and 3 2 < δ ij O(2 ) if i j. Notice that the terms 2 and O( 2 ) come exclsively from the pper bonds on ɛ k, ɛ k, ɛ k. By sing the refined bond E 1(t) /(1 + ) from (1.2) instead of jst E 1 (t), these pper bonds are straightforwardly improved to ɛ k ( )2 1 < 2 and ɛ k, ɛ k ( )3/2 1 < 3 2. Conseqently, Wilkinson s bonds in (5.3) can be replaced by the following more concise and slightly sharper ones: δ ii < 2 and δ ij < 3 2 if i j Example 3: Eclidean norm of an n-dimensional vector. Given a vector [x 1,..., x n ] T F n, let its norm r = x x2 n be evalated in floating point in the sal way: form the sqares fl(x 2 i ), sm them p in any order into ŝ, and retrn r = fl ( ŝ ). By applying the sal bond E 1 (t), all we can say is ŝ = ( n x2 i )(1 + θ n) with θ n as in (5.1), and r = ŝ (1 + δ) with δ. Conseqently, r = r(1 + ɛ), where ɛ = 1 + θ n (1 + δ) 1 satisfies (1 ) n/2+1 1 ɛ (1 + ) n/ Althogh the lower bond has absolte vale at most (n/2+1) see for example [4, p. 42], the pper bond is strictly larger than this, so that (5.4) (n/2 + 1) ɛ (n/2 + 1) + O( 2 ). To avoid the O( 2 ) term above, we can se the refined bond E 1 (t) /(1 + ), which says δ /(1 + ), together with the improved bond for inner prodcts from [10], which says θ n n. Indeed, from these two bonds we dedce that ɛ

14 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 13 is pper bonded by 1 + n (1 + /(1 + )) 1, and the latter qantity is easily checked to be at most (n/2 + 1). Ths, recalling the lower bond in (5.4), we conclde that (5.5) ɛ (n/2 + 1). In particlar, evalating the hypotense x x2 2 in floating-point prodces a relative error of at most 2; this improves over the classical bond 2 + O( 2 ), stated for example in [7, p. 225]. Of corse, the bond in (5.5) also applies when scaling by integer powers of the base is introdced to avoid nderflow and overflow Example 4: Cholesky factorization. We consider A F n n symmetric and its trianglarization in floating-point arithmetic sing the classical Cholesky algorithm. If the algorithm rns to completion, then by sing the bonds E i (t), i = 1, 2, the traditional ronding error analysis concldes that the compted factor R satisfies R T R = A + A with A γ n+1 R T R ; see for example [5, Theorem 10.3]. Here γ n+1 = (n+1) 1 (n+1) has the form (n + 1) + O( 2 ) and reqires n + 1 < 1. It was shown in [15] that both the qadratic term in and the restriction on n can be removed, reslting in the improved backward error bond A (n + 1) R T R. In the proof of [15, Theorem 4.4], one of the ingredients sed to sppress the O( 2 ) term is the following property: ( (5.6) a F 0 and b = fl ( a )) b 2 a 2b 2. In [15] it is shown that this property may not hold if only the bond E 2 (t) is assmed, and that in this case all we can say is (2 + 2 )b 2 b 2 a 2b 2. Frthermore, a proof of (5.6) is given, which is abot 10 lines long and based on a fp-based case analysis; see [15, p. 692]. Instead, or optimal bond on E 2 for sqare root provides a direct proof: Theorem 3.4 gives b(1 + δ) = a with δ ; hence b 2 a = b 2 2δ + δ 2 and 2δ + δ 2 (2 + δ ) δ ( )( ) = 2, from which (5.6) follows immediately Example 5: Complex mltiplication with an FMA. Given a, b, c, d F, consider the complex prodct z = (a + ib)(c + id). Varios approximations ẑ = R + i Î to z can be obtained, depending on how R = ac bd and I = ad + bc are evalated in floating-point. It was shown in [1] that the conventional way, which ses 4 mltiplications and 2 additions, gives ẑ = z(1 + ɛ) with ɛ C sch that ɛ < 5, and that the constant 5 is, at least in base 2, best possible. Assme now that an FMA is available, so that we compte, say, R = fl(ac fl(bd)) and Î = fl(ad + fl(bc)).

15 14 C.-P. JEANNEROD AND S. M. RUMP For this algorithm and its variants 3 it was shown in [8] that the bond 5 can be redced frther to 2, and that the latter is essentially optimal. The fact that 2 is an pper bond is established in [8, Theorem 3.1] with a rather long proof. As we shall see in the paragraph below, a mch more direct proof follows from simply applying the refined bond E 1 (t) /(1 + ) in a systematic way. Denoting by δ 1,..., δ 4 the for ronding errors involved, we have R = (ac bd(1 + δ 1 ))(1 + δ 2 ) = R + Rδ 2 bdδ 1 (1 + δ 2 ) and, similarly, Î = I + Iδ 4 + bcδ 3 (1 + δ 4 ). Now let λ, µ R 0 be sch that δ 2, δ 4 λ and δ 1 (1 + δ 2 ), δ 3 (1 + δ 4 ) µ. This implies that R R λ R + µ bd and I Î λ I + µ bc, from which we dedce (5.7) z ẑ 2 = (R R) 2 + (I Î)2 λ 2 z 2 + 2λµA + µ 2 B, where A = R bd + I bc and B = (bd) 2 + (bc) 2. It trns ot that (5.8) A, B z 2. For B, this bond simply follows from the eqality z 2 = (ac) 2 +(bd) 2 +(ad) 2 +(bc) 2. For A, define π = abcd and notice that A = π (bd) 2 + π + (bc) 2 is eqal to either B or ±(2π + (bc) 2 (bd) 2 ); frthermore, in the latter case we have A 2 π + (bc) 2 (bd) 2 min { (ac) 2 + (bd) 2, (ad) 2 + (bc) 2} + max { (bc) 2, (bd) 2} z 2. Ths, combining (5.7) and (5.8), z ẑ (λ + µ) z. Since the refined bond E 1 (t) /(1 + ) implies δ i /(1 + ) for all i, we can take λ = /(1 + ) and µ = /(1 + ) (1 + /(1 + )), which are both less than. Hence, barring nderflow and overflow and since z = 0 implies ẑ = 0, we conclde that ẑ = z(1 + ɛ), ɛ 2+32 (1+) 2 < 2. Note that 2+32 (1+) has the form O( 4 ) as 0. Ths, or approach 2 not only yields a shorter and more direct proof of the bond 2 of [8], bt it also improves on that bond. Appendix A. Proof that p as in (3.4) is not a power of two If j {5, 6, 7}, then p {144, 175, 206} and is not a power of two. Assme now that j 8. Writing d = 4m + i for integers m, i with 0 i 3, we have 4m + i log 2 k 4m + i If i 0, this implies 2 m+1/8 k 2 m+7/8 and then 2 m+1/8 4m + 10 p 2 m+7/8 4m There are three other ways to insert the innermost ronding fl, all giving the same error as the one developed here.

16 OPTIMAL BOUNDS ON RELATIVE ERRORS, WITH APPLICATIONS 15 Since the assmption j 8 implies k 2 8 and ths m 8, it follows that 2 m < p < 2 m+1. Conseqently, p cannot be a power of two when i 0. On the other hand, when i = 0, we see that p = 32j 4m + 13 mst be odd, and ths cannot be a power of two neither. Appendix B. Proof of Theorem 4.1 The lower bond follows from (4.1) and the triangle ineqality. For the pper bond, the proof is by indction on n, the case n = 1 being trivial (since then there is no ronding error at all). For n 2, we assme that the reslt is tre p to n 1, and we fix one evalation order in dimension n. The approximation ŝ obtained with this order has the form ŝ = fl(ŝ 1 + ŝ 2 ), where ŝ j is the reslt of a floating-point evalation of s j = i I j x i for j = 1, 2 and with {I 1, I 2 } a partition of the set I = {1, 2,..., n}. For j = 1, 2 let n j be the cardinality of I j and let e (1) j,..., e (nj 1) j be the ronding errors committed when evalating s j, so that s j = i<n j e (i) j + ŝ j. Conseqently, e i = δ , δ = ŝ 1 + ŝ 2 fl(ŝ 1 + ŝ 2 ). i<n i<n i<n 1 e (i) i<n 2 e (i) Since 1 n j < n, the indctive assmption leads to e i δ + ) ((n 1 1) s 1 + (n 2 1) s 2, 1 + where s j = i I j x i for j = 1, 2. Since n = n 1 + n 2 and n x i = s 1 + s 2, it remains to check that (B.1) δ 1 + (n 2 s 1 + n 1 s 2 ). To do so, we note that (1.2) and [10, Lemma 2.2] imply that { } δ min ŝ 1, ŝ 2, 1 + ŝ 1 + ŝ 2, and we consider the following three cases. Assme first that s 2 /(1 + ) s 1. Then s 2 s 1 and, sing δ ŝ 2, we obtain δ ŝ 2 s 2 + s 2 i<n 2 e (i) 2 + s 2 (n 2 1) 1 + s s 1 n s 1 and (B.1) ths follows. Second, when s 1 /(1+) s 2 we proceed similarly, simply swapping the indices 1 and 2. Third, when /(1+) s 1 < s 2 and /(1+) s 2 < s 1, we have δ /(1 + ) ŝ 1 + ŝ 2 with ŝ 1 + ŝ 2 ŝ 1 s 1 + s 1 + ŝ 2 s 2 + s 2 and ŝ j s j (n j 1)/(1 + ) s j (n j 1) s k for (j, k) {(1, 2), (2, 1)}. Hence (B.1) follows in this third case as well, ths completing the proof of Theorem 4.1.

17 16 C.-P. JEANNEROD AND S. M. RUMP References [1] R. Brent, C. Percival, and P. Zimmermann, Error bonds on complex floating-point mltiplication, Math. Comp. 76 (2007), [2] T. J. Dekker, A floating-point techniqe for extending the available precision, Nmer. Math. 18 (1971/72), [3] R. L. Graham, D. E. Knth, and O. Patashnik, Concrete Mathematics: A Fondation for Compter Science, 2nd ed., Addison-Wesley, Reading, MA, [4] G. H. Hardy, J. E. Littlewood, and G. Pólya, Ineqalities, 2nd ed., Cambridge University Press, Cambridge, UK, [5] N. J. Higham, Accracy and Stability of Nmerical Algorithms, 2nd ed., Society for Indstrial and Applied Mathematics (SIAM), Philadelphia, PA, [6] J. E. Holm, Floating-Point Arithmetic and Program Correctness Proofs, Ph.D. thesis, Cornell University, Ithaca, NY, Agst 1980, pp. vii+133. [7] T. E. Hll, T. F. Fairgrieve, and P. T. P. Tang, Implementing complex elementary fnctions sing exception handling, ACM Trans. Math. Software 20 (1994), no. 2, [8] C.-P. Jeannerod, P. Kornerp, N. Lovet, and J.-M. Mller, Error bonds on complex floating-point mltiplication with an FMA, Math. Comp. (pblished electronically), [9] C.-P. Jeannerod, N. Lovet, J.-M. Mller, and A. Panhalex, Midpoints and exact points of some algebraic fnctions in floating-point arithmetic, IEEE Trans. Compt. 60 (2011), no. 2, [10] C.-P. Jeannerod and S. M. Rmp, Improved error bonds for inner prodcts in floating-point arithmetic, SIAM J. Matrix Anal. Appl. 34 (2013), no. 2, [11] W. Keller, Prime factors k 2 n + 1 of Fermat nmbers F m and complete factoring stats, Agst 2016, web page available at [12] D. E. Knth, The Art of Compter Programming, Volme 2, Seminmerical Algorithms, 3rd ed., Addison-Wesley, Reading, MA, [13] P. W. Markstein, Comptation of elementary fnctions on the IBM RISC System/6000 processor, IBM Jornal of Research and Development 34 (1990), no. 1, [14] T. Ogita, S. M. Rmp, and S. Oishi, Accrate sm and dot prodct, SIAM J. Sci. Compt. 26 (2005), no. 6, [15] S. M. Rmp and C.-P. Jeannerod, Improved backward error bonds for LU and Cholesky factorizations, SIAM J. Matrix Anal. Appl. 35 (2014), no. 2, [16] S. M. Rmp, T. Ogita, and S. Oishi, Accrate floating-point smmation part I: Faithfl ronding, SIAM J. Sci. Compt. 31 (2008), no. 1, [17] N. J. A. Sloane and D. W. Wilson, Seqence A019434, The On-Line Encyclopedia of Integer Seqences, pblished electronically at [18] P. H. Sterbenz, Floating-Point Comptation, Prentice-Hall, [19] J. H. Wilkinson, Error analysis of floating-point comptation, Nmer. Math. 2 (1960), Inria and Université de Lyon, laboratoire LIP (CNRS, ENS de Lyon, Inria, UCBL), 46 allée d Italie Lyon cedex 07, France address: clade-pierre.jeannerod@inria.fr Hambrg University of Technology, Schwarzenbergstraße 95, Hambrg 21071, Germany, and Faclty of Science and Engineering, Waseda University, Okbo, Shinjkk, Tokyo , Japan address: rmp@thh.de

On relative errors of floating-point operations: optimal bounds and applications

On relative errors of floating-point operations: optimal bounds and applications On relative errors of floating-point operations: optimal bonds and applications Clade-Pierre Jeannerod, Siegfried M. Rmp To cite this version: Clade-Pierre Jeannerod, Siegfried M. Rmp. On relative errors

More information

Worst-case analysis of the LPT algorithm for single processor scheduling with time restrictions

Worst-case analysis of the LPT algorithm for single processor scheduling with time restrictions OR Spectrm 06 38:53 540 DOI 0.007/s009-06-043-5 REGULAR ARTICLE Worst-case analysis of the LPT algorithm for single processor schedling with time restrictions Oliver ran Fan Chng Ron Graham Received: Janary

More information

Constructive Root Bound for k-ary Rational Input Numbers

Constructive Root Bound for k-ary Rational Input Numbers Constrctive Root Bond for k-ary Rational Inpt Nmbers Sylvain Pion, Chee Yap To cite this version: Sylvain Pion, Chee Yap. Constrctive Root Bond for k-ary Rational Inpt Nmbers. 19th Annal ACM Symposim on

More information

On the circuit complexity of the standard and the Karatsuba methods of multiplying integers

On the circuit complexity of the standard and the Karatsuba methods of multiplying integers On the circit complexity of the standard and the Karatsba methods of mltiplying integers arxiv:1602.02362v1 [cs.ds] 7 Feb 2016 Igor S. Sergeev The goal of the present paper is to obtain accrate estimates

More information

Section 7.4: Integration of Rational Functions by Partial Fractions

Section 7.4: Integration of Rational Functions by Partial Fractions Section 7.4: Integration of Rational Fnctions by Partial Fractions This is abot as complicated as it gets. The Method of Partial Fractions Ecept for a few very special cases, crrently we have no way to

More information

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2 MATH 307 Vectors in Rn Dr. Neal, WKU Matrices of dimension 1 n can be thoght of as coordinates, or ectors, in n- dimensional space R n. We can perform special calclations on these ectors. In particlar,

More information

Classify by number of ports and examine the possible structures that result. Using only one-port elements, no more than two elements can be assembled.

Classify by number of ports and examine the possible structures that result. Using only one-port elements, no more than two elements can be assembled. Jnction elements in network models. Classify by nmber of ports and examine the possible strctres that reslt. Using only one-port elements, no more than two elements can be assembled. Combining two two-ports

More information

The Lehmer matrix and its recursive analogue

The Lehmer matrix and its recursive analogue The Lehmer matrix and its recrsive analoge Emrah Kilic, Pantelimon Stănică TOBB Economics and Technology University, Mathematics Department 0660 Sogtoz, Ankara, Trkey; ekilic@etedtr Naval Postgradate School,

More information

Nonlinear parametric optimization using cylindrical algebraic decomposition

Nonlinear parametric optimization using cylindrical algebraic decomposition Proceedings of the 44th IEEE Conference on Decision and Control, and the Eropean Control Conference 2005 Seville, Spain, December 12-15, 2005 TC08.5 Nonlinear parametric optimization sing cylindrical algebraic

More information

B-469 Simplified Copositive and Lagrangian Relaxations for Linearly Constrained Quadratic Optimization Problems in Continuous and Binary Variables

B-469 Simplified Copositive and Lagrangian Relaxations for Linearly Constrained Quadratic Optimization Problems in Continuous and Binary Variables B-469 Simplified Copositive and Lagrangian Relaxations for Linearly Constrained Qadratic Optimization Problems in Continos and Binary Variables Naohiko Arima, Snyong Kim and Masakaz Kojima October 2012,

More information

4.2 First-Order Logic

4.2 First-Order Logic 64 First-Order Logic and Type Theory The problem can be seen in the two qestionable rles In the existential introdction, the term a has not yet been introdced into the derivation and its se can therefore

More information

Cubic graphs have bounded slope parameter

Cubic graphs have bounded slope parameter Cbic graphs have bonded slope parameter B. Keszegh, J. Pach, D. Pálvölgyi, and G. Tóth Agst 25, 2009 Abstract We show that every finite connected graph G with maximm degree three and with at least one

More information

The Cryptanalysis of a New Public-Key Cryptosystem based on Modular Knapsacks

The Cryptanalysis of a New Public-Key Cryptosystem based on Modular Knapsacks The Cryptanalysis of a New Pblic-Key Cryptosystem based on Modlar Knapsacks Yeow Meng Chee Antoine Jox National Compter Systems DMI-GRECC Center for Information Technology 45 re d Ulm 73 Science Park Drive,

More information

Lecture Notes: Finite Element Analysis, J.E. Akin, Rice University

Lecture Notes: Finite Element Analysis, J.E. Akin, Rice University 9. TRUSS ANALYSIS... 1 9.1 PLANAR TRUSS... 1 9. SPACE TRUSS... 11 9.3 SUMMARY... 1 9.4 EXERCISES... 15 9. Trss analysis 9.1 Planar trss: The differential eqation for the eqilibrim of an elastic bar (above)

More information

On the tree cover number of a graph

On the tree cover number of a graph On the tree cover nmber of a graph Chassidy Bozeman Minerva Catral Brendan Cook Oscar E. González Carolyn Reinhart Abstract Given a graph G, the tree cover nmber of the graph, denoted T (G), is the minimm

More information

OPTIMUM EXPRESSION FOR COMPUTATION OF THE GRAVITY FIELD OF A POLYHEDRAL BODY WITH LINEARLY INCREASING DENSITY 1

OPTIMUM EXPRESSION FOR COMPUTATION OF THE GRAVITY FIELD OF A POLYHEDRAL BODY WITH LINEARLY INCREASING DENSITY 1 OPTIMUM EXPRESSION FOR COMPUTATION OF THE GRAVITY FIEL OF A POLYHERAL BOY WITH LINEARLY INCREASING ENSITY 1 V. POHÁNKA2 Abstract The formla for the comptation of the gravity field of a polyhedral body

More information

Lecture Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2

Lecture Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2 BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA Lectre Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2 Prepared by, Dr. Sbhend Kmar Rath, BPUT, Odisha. Tring Machine- Miscellany UNIT 2 TURING MACHINE

More information

FOUNTAIN codes [3], [4] provide an efficient solution

FOUNTAIN codes [3], [4] provide an efficient solution Inactivation Decoding of LT and Raptor Codes: Analysis and Code Design Francisco Lázaro, Stdent Member, IEEE, Gianligi Liva, Senior Member, IEEE, Gerhard Bach, Fellow, IEEE arxiv:176.5814v1 [cs.it 19 Jn

More information

Decoder Error Probability of MRD Codes

Decoder Error Probability of MRD Codes Decoder Error Probability of MRD Codes Maximilien Gadolea Department of Electrical and Compter Engineering Lehigh University Bethlehem, PA 18015 USA E-mail: magc@lehighed Zhiyan Yan Department of Electrical

More information

Discontinuous Fluctuation Distribution for Time-Dependent Problems

Discontinuous Fluctuation Distribution for Time-Dependent Problems Discontinos Flctation Distribtion for Time-Dependent Problems Matthew Hbbard School of Compting, University of Leeds, Leeds, LS2 9JT, UK meh@comp.leeds.ac.k Introdction For some years now, the flctation

More information

CHANNEL SELECTION WITH RAYLEIGH FADING: A MULTI-ARMED BANDIT FRAMEWORK. Wassim Jouini and Christophe Moy

CHANNEL SELECTION WITH RAYLEIGH FADING: A MULTI-ARMED BANDIT FRAMEWORK. Wassim Jouini and Christophe Moy CHANNEL SELECTION WITH RAYLEIGH FADING: A MULTI-ARMED BANDIT FRAMEWORK Wassim Joini and Christophe Moy SUPELEC, IETR, SCEE, Avene de la Bolaie, CS 47601, 5576 Cesson Sévigné, France. INSERM U96 - IFR140-

More information

Chapter 2 Difficulties associated with corners

Chapter 2 Difficulties associated with corners Chapter Difficlties associated with corners This chapter is aimed at resolving the problems revealed in Chapter, which are cased b corners and/or discontinos bondar conditions. The first section introdces

More information

UNCERTAINTY FOCUSED STRENGTH ANALYSIS MODEL

UNCERTAINTY FOCUSED STRENGTH ANALYSIS MODEL 8th International DAAAM Baltic Conference "INDUSTRIAL ENGINEERING - 19-1 April 01, Tallinn, Estonia UNCERTAINTY FOCUSED STRENGTH ANALYSIS MODEL Põdra, P. & Laaneots, R. Abstract: Strength analysis is a

More information

1 The space of linear transformations from R n to R m :

1 The space of linear transformations from R n to R m : Math 540 Spring 20 Notes #4 Higher deriaties, Taylor s theorem The space of linear transformations from R n to R m We hae discssed linear transformations mapping R n to R m We can add sch linear transformations

More information

Introdction Finite elds play an increasingly important role in modern digital commnication systems. Typical areas of applications are cryptographic sc

Introdction Finite elds play an increasingly important role in modern digital commnication systems. Typical areas of applications are cryptographic sc A New Architectre for a Parallel Finite Field Mltiplier with Low Complexity Based on Composite Fields Christof Paar y IEEE Transactions on Compters, Jly 996, vol 45, no 7, pp 856-86 Abstract In this paper

More information

CONTENTS. INTRODUCTION MEQ curriculum objectives for vectors (8% of year). page 2 What is a vector? What is a scalar? page 3, 4

CONTENTS. INTRODUCTION MEQ curriculum objectives for vectors (8% of year). page 2 What is a vector? What is a scalar? page 3, 4 CONTENTS INTRODUCTION MEQ crriclm objectives for vectors (8% of year). page 2 What is a vector? What is a scalar? page 3, 4 VECTOR CONCEPTS FROM GEOMETRIC AND ALGEBRAIC PERSPECTIVES page 1 Representation

More information

The Brauer Manin obstruction

The Brauer Manin obstruction The Braer Manin obstrction Martin Bright 17 April 2008 1 Definitions Let X be a smooth, geometrically irredcible ariety oer a field k. Recall that the defining property of an Azmaya algebra A is that,

More information

CRITERIA FOR TOEPLITZ OPERATORS ON THE SPHERE. Jingbo Xia

CRITERIA FOR TOEPLITZ OPERATORS ON THE SPHERE. Jingbo Xia CRITERIA FOR TOEPLITZ OPERATORS ON THE SPHERE Jingbo Xia Abstract. Let H 2 (S) be the Hardy space on the nit sphere S in C n. We show that a set of inner fnctions Λ is sfficient for the prpose of determining

More information

Control Systems

Control Systems 6.5 Control Systems Last Time: Introdction Motivation Corse Overview Project Math. Descriptions of Systems ~ Review Classification of Systems Linear Systems LTI Systems The notion of state and state variables

More information

Decoder Error Probability of MRD Codes

Decoder Error Probability of MRD Codes Decoder Error Probability of MRD Codes Maximilien Gadolea Department of Electrical and Compter Engineering Lehigh University Bethlehem, PA 18015 USA E-mail: magc@lehigh.ed Zhiyan Yan Department of Electrical

More information

Pulses on a Struck String

Pulses on a Struck String 8.03 at ESG Spplemental Notes Plses on a Strck String These notes investigate specific eamples of transverse motion on a stretched string in cases where the string is at some time ndisplaced, bt with a

More information

Network Coding for Multiple Unicasts: An Approach based on Linear Optimization

Network Coding for Multiple Unicasts: An Approach based on Linear Optimization Network Coding for Mltiple Unicasts: An Approach based on Linear Optimization Danail Traskov, Niranjan Ratnakar, Desmond S. Ln, Ralf Koetter, and Mriel Médard Abstract In this paper we consider the application

More information

Move Blocking Strategies in Receding Horizon Control

Move Blocking Strategies in Receding Horizon Control Move Blocking Strategies in Receding Horizon Control Raphael Cagienard, Pascal Grieder, Eric C. Kerrigan and Manfred Morari Abstract In order to deal with the comptational brden of optimal control, it

More information

Fixed points for discrete logarithms

Fixed points for discrete logarithms Fixed points for discrete logarithms Mariana Levin 1, Carl Pomerance 2, and and K. Sondararajan 3 1 Gradate Grop in Science and Mathematics Edcation University of California Berkeley, CA 94720, USA levin@berkeley.ed

More information

The Dual of the Maximum Likelihood Method

The Dual of the Maximum Likelihood Method Department of Agricltral and Resorce Economics University of California, Davis The Dal of the Maximm Likelihood Method by Qirino Paris Working Paper No. 12-002 2012 Copyright @ 2012 by Qirino Paris All

More information

Formally Verified Approximations of Definite Integrals

Formally Verified Approximations of Definite Integrals Formally Verified Approximations of Definite Integrals Assia Mahbobi, Gillame Melqiond, Thomas Sibt-Pinote To cite this version: Assia Mahbobi, Gillame Melqiond, Thomas Sibt-Pinote. Formally Verified Approximations

More information

Subcritical bifurcation to innitely many rotating waves. Arnd Scheel. Freie Universitat Berlin. Arnimallee Berlin, Germany

Subcritical bifurcation to innitely many rotating waves. Arnd Scheel. Freie Universitat Berlin. Arnimallee Berlin, Germany Sbcritical bifrcation to innitely many rotating waves Arnd Scheel Institt fr Mathematik I Freie Universitat Berlin Arnimallee 2-6 14195 Berlin, Germany 1 Abstract We consider the eqation 00 + 1 r 0 k2

More information

Gradient Projection Anti-windup Scheme on Constrained Planar LTI Systems. Justin Teo and Jonathan P. How

Gradient Projection Anti-windup Scheme on Constrained Planar LTI Systems. Justin Teo and Jonathan P. How 1 Gradient Projection Anti-windp Scheme on Constrained Planar LTI Systems Jstin Teo and Jonathan P. How Technical Report ACL1 1 Aerospace Controls Laboratory Department of Aeronatics and Astronatics Massachsetts

More information

Formules relatives aux probabilités qui dépendent de très grands nombers

Formules relatives aux probabilités qui dépendent de très grands nombers Formles relatives ax probabilités qi dépendent de très grands nombers M. Poisson Comptes rends II (836) pp. 603-63 In the most important applications of the theory of probabilities, the chances of events

More information

A Note on Johnson, Minkoff and Phillips Algorithm for the Prize-Collecting Steiner Tree Problem

A Note on Johnson, Minkoff and Phillips Algorithm for the Prize-Collecting Steiner Tree Problem A Note on Johnson, Minkoff and Phillips Algorithm for the Prize-Collecting Steiner Tree Problem Palo Feofiloff Cristina G. Fernandes Carlos E. Ferreira José Coelho de Pina September 04 Abstract The primal-dal

More information

1. Tractable and Intractable Computational Problems So far in the course we have seen many problems that have polynomial-time solutions; that is, on

1. Tractable and Intractable Computational Problems So far in the course we have seen many problems that have polynomial-time solutions; that is, on . Tractable and Intractable Comptational Problems So far in the corse we have seen many problems that have polynomial-time soltions; that is, on a problem instance of size n, the rnning time T (n) = O(n

More information

Some extensions of Alon s Nullstellensatz

Some extensions of Alon s Nullstellensatz Some extensions of Alon s Nllstellensatz arxiv:1103.4768v2 [math.co] 15 Ag 2011 Géza Kós Compter and Atomation Research Institte, Hngarian Acad. Sci; Dept. of Analysis, Eötvös Loránd Univ., Bdapest kosgeza@szta.h

More information

Affine Invariant Total Variation Models

Affine Invariant Total Variation Models Affine Invariant Total Variation Models Helen Balinsky, Alexander Balinsky Media Technologies aboratory HP aboratories Bristol HP-7-94 Jne 6, 7* Total Variation, affine restoration, Sobolev ineqality,

More information

When are Two Numerical Polynomials Relatively Prime?

When are Two Numerical Polynomials Relatively Prime? J Symbolic Comptation (1998) 26, 677 689 Article No sy980234 When are Two Nmerical Polynomials Relatively Prime? BERNHARD BECKERMANN AND GEORGE LABAHN Laboratoire d Analyse Nmériqe et d Optimisation, Université

More information

A generalized Alon-Boppana bound and weak Ramanujan graphs

A generalized Alon-Boppana bound and weak Ramanujan graphs A generalized Alon-Boppana bond and weak Ramanjan graphs Fan Chng Abstract A basic eigenvale bond de to Alon and Boppana holds only for reglar graphs. In this paper we give a generalized Alon-Boppana bond

More information

Sign-reductions, p-adic valuations, binomial coefficients modulo p k and triangular symmetries

Sign-reductions, p-adic valuations, binomial coefficients modulo p k and triangular symmetries Sign-redctions, p-adic valations, binomial coefficients modlo p k and trianglar symmetries Mihai Prnesc Abstract According to a classical reslt of E. Kmmer, the p-adic valation v p applied to a binomial

More information

BLOOM S TAXONOMY. Following Bloom s Taxonomy to Assess Students

BLOOM S TAXONOMY. Following Bloom s Taxonomy to Assess Students BLOOM S TAXONOMY Topic Following Bloom s Taonomy to Assess Stdents Smmary A handot for stdents to eplain Bloom s taonomy that is sed for item writing and test constrction to test stdents to see if they

More information

Universal Scheme for Optimal Search and Stop

Universal Scheme for Optimal Search and Stop Universal Scheme for Optimal Search and Stop Sirin Nitinawarat Qalcomm Technologies, Inc. 5775 Morehose Drive San Diego, CA 92121, USA Email: sirin.nitinawarat@gmail.com Vengopal V. Veeravalli Coordinated

More information

The Linear Quadratic Regulator

The Linear Quadratic Regulator 10 The Linear Qadratic Reglator 10.1 Problem formlation This chapter concerns optimal control of dynamical systems. Most of this development concerns linear models with a particlarly simple notion of optimality.

More information

4 Exact laminar boundary layer solutions

4 Exact laminar boundary layer solutions 4 Eact laminar bondary layer soltions 4.1 Bondary layer on a flat plate (Blasis 1908 In Sec. 3, we derived the bondary layer eqations for 2D incompressible flow of constant viscosity past a weakly crved

More information

Assignment Fall 2014

Assignment Fall 2014 Assignment 5.086 Fall 04 De: Wednesday, 0 December at 5 PM. Upload yor soltion to corse website as a zip file YOURNAME_ASSIGNMENT_5 which incldes the script for each qestion as well as all Matlab fnctions

More information

A generalized Alon-Boppana bound and weak Ramanujan graphs

A generalized Alon-Boppana bound and weak Ramanujan graphs A generalized Alon-Boppana bond and weak Ramanjan graphs Fan Chng Department of Mathematics University of California, San Diego La Jolla, CA, U.S.A. fan@csd.ed Sbmitted: Feb 0, 206; Accepted: Jne 22, 206;

More information

Remarks on strongly convex stochastic processes

Remarks on strongly convex stochastic processes Aeqat. Math. 86 (01), 91 98 c The Athor(s) 01. This article is pblished with open access at Springerlink.com 0001-9054/1/010091-8 pblished online November 7, 01 DOI 10.1007/s00010-01-016-9 Aeqationes Mathematicae

More information

LINEAR COMBINATIONS AND SUBSPACES

LINEAR COMBINATIONS AND SUBSPACES CS131 Part II, Linear Algebra and Matrices CS131 Mathematics for Compter Scientists II Note 5 LINEAR COMBINATIONS AND SUBSPACES Linear combinations. In R 2 the vector (5, 3) can be written in the form

More information

Optimal Control of a Heterogeneous Two Server System with Consideration for Power and Performance

Optimal Control of a Heterogeneous Two Server System with Consideration for Power and Performance Optimal Control of a Heterogeneos Two Server System with Consideration for Power and Performance by Jiazheng Li A thesis presented to the University of Waterloo in flfilment of the thesis reqirement for

More information

Discussion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli

Discussion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli 1 Introdction Discssion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli Søren Johansen Department of Economics, University of Copenhagen and CREATES,

More information

The Classical Relative Error Bounds for Computing a2 + b 2 and c/ a 2 + b 2 in Binary Floating-Point Arithmetic are Asymptotically Optimal

The Classical Relative Error Bounds for Computing a2 + b 2 and c/ a 2 + b 2 in Binary Floating-Point Arithmetic are Asymptotically Optimal -1- The Classical Relative Error Bounds for Computing a2 + b 2 and c/ a 2 + b 2 in Binary Floating-Point Arithmetic are Asymptotically Optimal Claude-Pierre Jeannerod Jean-Michel Muller Antoine Plet Inria,

More information

Setting The K Value And Polarization Mode Of The Delta Undulator

Setting The K Value And Polarization Mode Of The Delta Undulator LCLS-TN-4- Setting The Vale And Polarization Mode Of The Delta Undlator Zachary Wolf, Heinz-Dieter Nhn SLAC September 4, 04 Abstract This note provides the details for setting the longitdinal positions

More information

A Characterization of Interventional Distributions in Semi-Markovian Causal Models

A Characterization of Interventional Distributions in Semi-Markovian Causal Models A Characterization of Interventional Distribtions in Semi-Markovian Casal Models Jin Tian and Changsng Kang Department of Compter Science Iowa State University Ames, IA 50011 {jtian, cskang}@cs.iastate.ed

More information

Convergence analysis of ant colony learning

Convergence analysis of ant colony learning Delft University of Technology Delft Center for Systems and Control Technical report 11-012 Convergence analysis of ant colony learning J van Ast R Babška and B De Schtter If yo want to cite this report

More information

Discussion Papers Department of Economics University of Copenhagen

Discussion Papers Department of Economics University of Copenhagen Discssion Papers Department of Economics University of Copenhagen No. 10-06 Discssion of The Forward Search: Theory and Data Analysis, by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli Søren Johansen,

More information

We automate the bivariate change-of-variables technique for bivariate continuous random variables with

We automate the bivariate change-of-variables technique for bivariate continuous random variables with INFORMS Jornal on Compting Vol. 4, No., Winter 0, pp. 9 ISSN 09-9856 (print) ISSN 56-558 (online) http://dx.doi.org/0.87/ijoc.046 0 INFORMS Atomating Biariate Transformations Jeff X. Yang, John H. Drew,

More information

A Regulator for Continuous Sedimentation in Ideal Clarifier-Thickener Units

A Regulator for Continuous Sedimentation in Ideal Clarifier-Thickener Units A Reglator for Continos Sedimentation in Ideal Clarifier-Thickener Units STEFAN DIEHL Centre for Mathematical Sciences, Lnd University, P.O. Box, SE- Lnd, Sweden e-mail: diehl@maths.lth.se) Abstract. The

More information

Conditions for Approaching the Origin without Intersecting the x-axis in the Liénard Plane

Conditions for Approaching the Origin without Intersecting the x-axis in the Liénard Plane Filomat 3:2 (27), 376 377 https://doi.org/.2298/fil7276a Pblished by Faclty of Sciences and Mathematics, University of Niš, Serbia Available at: http://www.pmf.ni.ac.rs/filomat Conditions for Approaching

More information

A note on the computation of the fraction of smallest denominator in between two irreducible fractions

A note on the computation of the fraction of smallest denominator in between two irreducible fractions A note on the computation of the fraction of smallest denominator in between two irreducible fractions Isabelle Sivignon To cite this version: Isabelle Sivignon. A note on the computation of the fraction

More information

A Note on Irreducible Polynomials and Identity Testing

A Note on Irreducible Polynomials and Identity Testing A Note on Irrecible Polynomials an Ientity Testing Chanan Saha Department of Compter Science an Engineering Inian Institte of Technology Kanpr Abstract We show that, given a finite fiel F q an an integer

More information

Graph-Modeled Data Clustering: Fixed-Parameter Algorithms for Clique Generation

Graph-Modeled Data Clustering: Fixed-Parameter Algorithms for Clique Generation Graph-Modeled Data Clstering: Fied-Parameter Algorithms for Cliqe Generation Jens Gramm Jiong Go Falk Hüffner Rolf Niedermeier Wilhelm-Schickard-Institt für Informatik, Universität Tübingen, Sand 13, D-72076

More information

3.1 The Basic Two-Level Model - The Formulas

3.1 The Basic Two-Level Model - The Formulas CHAPTER 3 3 THE BASIC MULTILEVEL MODEL AND EXTENSIONS In the previos Chapter we introdced a nmber of models and we cleared ot the advantages of Mltilevel Models in the analysis of hierarchically nested

More information

Technical Note. ODiSI-B Sensor Strain Gage Factor Uncertainty

Technical Note. ODiSI-B Sensor Strain Gage Factor Uncertainty Technical Note EN-FY160 Revision November 30, 016 ODiSI-B Sensor Strain Gage Factor Uncertainty Abstract Lna has pdated or strain sensor calibration tool to spport NIST-traceable measrements, to compte

More information

Scheduling parallel jobs to minimize the makespan

Scheduling parallel jobs to minimize the makespan J Sched (006) 9:433 45 DOI 10.1007/s10951-006-8497-6 Schedling parallel jobs to minimize the makespan Berit Johannes C Springer Science + Bsiness Media, LLC 006 Abstract We consider the NP-hard problem

More information

Lecture 3. (2) Last time: 3D space. The dot product. Dan Nichols January 30, 2018

Lecture 3. (2) Last time: 3D space. The dot product. Dan Nichols January 30, 2018 Lectre 3 The dot prodct Dan Nichols nichols@math.mass.ed MATH 33, Spring 018 Uniersity of Massachsetts Janary 30, 018 () Last time: 3D space Right-hand rle, the three coordinate planes 3D coordinate system:

More information

arxiv: v2 [cs.ds] 17 Oct 2014

arxiv: v2 [cs.ds] 17 Oct 2014 On Uniform Capacitated k-median Beyond the Natral LP Relaxation Shi Li Toyota Technological Institte at Chicago shili@ttic.ed arxiv:1409.6739v2 [cs.ds] 17 Oct 2014 Abstract In this paper, we stdy the niform

More information

Graphs and Their. Applications (6) K.M. Koh* F.M. Dong and E.G. Tay. 17 The Number of Spanning Trees

Graphs and Their. Applications (6) K.M. Koh* F.M. Dong and E.G. Tay. 17 The Number of Spanning Trees Graphs and Their Applications (6) by K.M. Koh* Department of Mathematics National University of Singapore, Singapore 1 ~ 7543 F.M. Dong and E.G. Tay Mathematics and Mathematics EdOOation National Institte

More information

Lesson 81: The Cross Product of Vectors

Lesson 81: The Cross Product of Vectors Lesson 8: The Cross Prodct of Vectors IBHL - SANTOWSKI In this lesson yo will learn how to find the cross prodct of two ectors how to find an orthogonal ector to a plane defined by two ectors how to find

More information

L 1 -smoothing for the Ornstein-Uhlenbeck semigroup

L 1 -smoothing for the Ornstein-Uhlenbeck semigroup L -smoothing for the Ornstein-Uhlenbeck semigrop K. Ball, F. Barthe, W. Bednorz, K. Oleszkiewicz and P. Wolff September, 00 Abstract Given a probability density, we estimate the rate of decay of the measre

More information

The Heat Equation and the Li-Yau Harnack Inequality

The Heat Equation and the Li-Yau Harnack Inequality The Heat Eqation and the Li-Ya Harnack Ineqality Blake Hartley VIGRE Research Paper Abstract In this paper, we develop the necessary mathematics for nderstanding the Li-Ya Harnack ineqality. We begin with

More information

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions Chem 4501 Introdction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics Fall Semester 2017 Homework Problem Set Nmber 10 Soltions 1. McQarrie and Simon, 10-4. Paraphrase: Apply Eler s theorem

More information

Applying Fuzzy Set Approach into Achieving Quality Improvement for Qualitative Quality Response

Applying Fuzzy Set Approach into Achieving Quality Improvement for Qualitative Quality Response Proceedings of the 007 WSES International Conference on Compter Engineering and pplications, Gold Coast, stralia, Janary 17-19, 007 5 pplying Fzzy Set pproach into chieving Qality Improvement for Qalitative

More information

Analysis of the average depth in a suffix tree under a Markov model

Analysis of the average depth in a suffix tree under a Markov model Analysis of the average depth in a sffix tree nder a Markov model Jlien Fayolle, Mark Daniel Ward To cite this version: Jlien Fayolle, Mark Daniel Ward. Analysis of the average depth in a sffix tree nder

More information

MAXIMUM AND ANTI-MAXIMUM PRINCIPLES FOR THE P-LAPLACIAN WITH A NONLINEAR BOUNDARY CONDITION. 1. Introduction. ν = λ u p 2 u.

MAXIMUM AND ANTI-MAXIMUM PRINCIPLES FOR THE P-LAPLACIAN WITH A NONLINEAR BOUNDARY CONDITION. 1. Introduction. ν = λ u p 2 u. 2005-Ojda International Conference on Nonlinear Analysis. Electronic Jornal of Differential Eqations, Conference 14, 2006, pp. 95 107. ISSN: 1072-6691. URL: http://ejde.math.txstate.ed or http://ejde.math.nt.ed

More information

PhysicsAndMathsTutor.com

PhysicsAndMathsTutor.com C Integration - By sbstittion PhysicsAndMathsTtor.com. Using the sbstittion cos +, or otherwise, show that e cos + sin d e(e ) (Total marks). (a) Using the sbstittion cos, or otherwise, find the eact vale

More information

Prediction of Transmission Distortion for Wireless Video Communication: Analysis

Prediction of Transmission Distortion for Wireless Video Communication: Analysis Prediction of Transmission Distortion for Wireless Video Commnication: Analysis Zhifeng Chen and Dapeng W Department of Electrical and Compter Engineering, University of Florida, Gainesville, Florida 326

More information

An Investigation into Estimating Type B Degrees of Freedom

An Investigation into Estimating Type B Degrees of Freedom An Investigation into Estimating Type B Degrees of H. Castrp President, Integrated Sciences Grop Jne, 00 Backgrond The degrees of freedom associated with an ncertainty estimate qantifies the amont of information

More information

Department of Industrial Engineering Statistical Quality Control presented by Dr. Eng. Abed Schokry

Department of Industrial Engineering Statistical Quality Control presented by Dr. Eng. Abed Schokry Department of Indstrial Engineering Statistical Qality Control presented by Dr. Eng. Abed Schokry Department of Indstrial Engineering Statistical Qality Control C and U Chart presented by Dr. Eng. Abed

More information

Second-Order Wave Equation

Second-Order Wave Equation Second-Order Wave Eqation A. Salih Department of Aerospace Engineering Indian Institte of Space Science and Technology, Thirvananthapram 3 December 016 1 Introdction The classical wave eqation is a second-order

More information

9. Tensor product and Hom

9. Tensor product and Hom 9. Tensor prodct and Hom Starting from two R-modles we can define two other R-modles, namely M R N and Hom R (M, N), that are very mch related. The defining properties of these modles are simple, bt those

More information

Characterizations of probability distributions via bivariate regression of record values

Characterizations of probability distributions via bivariate regression of record values Metrika (2008) 68:51 64 DOI 10.1007/s00184-007-0142-7 Characterizations of probability distribtions via bivariate regression of record vales George P. Yanev M. Ahsanllah M. I. Beg Received: 4 October 2006

More information

Approximate Solution for the System of Non-linear Volterra Integral Equations of the Second Kind by using Block-by-block Method

Approximate Solution for the System of Non-linear Volterra Integral Equations of the Second Kind by using Block-by-block Method Astralian Jornal of Basic and Applied Sciences, (1): 114-14, 008 ISSN 1991-8178 Approximate Soltion for the System of Non-linear Volterra Integral Eqations of the Second Kind by sing Block-by-block Method

More information

Floating Point Arithmetic and Rounding Error Analysis

Floating Point Arithmetic and Rounding Error Analysis Floating Point Arithmetic and Rounding Error Analysis Claude-Pierre Jeannerod Nathalie Revol Inria LIP, ENS de Lyon 2 Context Starting point: How do numerical algorithms behave in nite precision arithmetic?

More information

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n 12.4 The Cross Prodct 873 12.4 The Cross Prodct In stdying lines in the plane, when we needed to describe how a line was tilting, we sed the notions of slope and angle of inclination. In space, we want

More information

Sensitivity Analysis in Bayesian Networks: From Single to Multiple Parameters

Sensitivity Analysis in Bayesian Networks: From Single to Multiple Parameters Sensitivity Analysis in Bayesian Networks: From Single to Mltiple Parameters Hei Chan and Adnan Darwiche Compter Science Department University of California, Los Angeles Los Angeles, CA 90095 {hei,darwiche}@cs.cla.ed

More information

Sources of Non Stationarity in the Semivariogram

Sources of Non Stationarity in the Semivariogram Sorces of Non Stationarity in the Semivariogram Migel A. Cba and Oy Leangthong Traditional ncertainty characterization techniqes sch as Simple Kriging or Seqential Gassian Simlation rely on stationary

More information

Exact Comparison of Quadratic Irrationals

Exact Comparison of Quadratic Irrationals Exact Comparison of Quadratic Irrationals Phuc Ngo To cite this version: Phuc Ngo. Exact Comparison of Quadratic Irrationals. [Research Report] LIGM. 20. HAL Id: hal-0069762 https://hal.archives-ouvertes.fr/hal-0069762

More information

Stability of Model Predictive Control using Markov Chain Monte Carlo Optimisation

Stability of Model Predictive Control using Markov Chain Monte Carlo Optimisation Stability of Model Predictive Control sing Markov Chain Monte Carlo Optimisation Elilini Siva, Pal Golart, Jan Maciejowski and Nikolas Kantas Abstract We apply stochastic Lyapnov theory to perform stability

More information

RELIABILITY ASPECTS OF PROPORTIONAL MEAN RESIDUAL LIFE MODEL USING QUANTILE FUNC- TIONS

RELIABILITY ASPECTS OF PROPORTIONAL MEAN RESIDUAL LIFE MODEL USING QUANTILE FUNC- TIONS RELIABILITY ASPECTS OF PROPORTIONAL MEAN RESIDUAL LIFE MODEL USING QUANTILE FUNC- TIONS Athors: N.UNNIKRISHNAN NAIR Department of Statistics, Cochin University of Science Technology, Cochin, Kerala, INDIA

More information

The Replenishment Policy for an Inventory System with a Fixed Ordering Cost and a Proportional Penalty Cost under Poisson Arrival Demands

The Replenishment Policy for an Inventory System with a Fixed Ordering Cost and a Proportional Penalty Cost under Poisson Arrival Demands Scientiae Mathematicae Japonicae Online, e-211, 161 167 161 The Replenishment Policy for an Inventory System with a Fixed Ordering Cost and a Proportional Penalty Cost nder Poisson Arrival Demands Hitoshi

More information

CONSIDER an array of N sensors (residing in threedimensional. Investigating Hyperhelical Array Manifold Curves Using the Complex Cartan Matrix

CONSIDER an array of N sensors (residing in threedimensional. Investigating Hyperhelical Array Manifold Curves Using the Complex Cartan Matrix IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (SPECIAL ISSUE), VOL.?, NO.?,???? 1 Investigating yperhelical Array Manifold Crves Using the Complex Cartan Matrix Athanassios Manikas, Senior Member,

More information

AN ISOGEOMETRIC SOLID-SHELL FORMULATION OF THE KOITER METHOD FOR BUCKLING AND INITIAL POST-BUCKLING ANALYSIS OF COMPOSITE SHELLS

AN ISOGEOMETRIC SOLID-SHELL FORMULATION OF THE KOITER METHOD FOR BUCKLING AND INITIAL POST-BUCKLING ANALYSIS OF COMPOSITE SHELLS th Eropean Conference on Comptational Mechanics (ECCM ) 7th Eropean Conference on Comptational Flid Dynamics (ECFD 7) 5 Jne 28, Glasgow, UK AN ISOGEOMETRIC SOLID-SHELL FORMULATION OF THE KOITER METHOD

More information

Elements of Coordinate System Transformations

Elements of Coordinate System Transformations B Elements of Coordinate System Transformations Coordinate system transformation is a powerfl tool for solving many geometrical and kinematic problems that pertain to the design of gear ctting tools and

More information

On oriented arc-coloring of subcubic graphs

On oriented arc-coloring of subcubic graphs On oriented arc-coloring of sbcbic graphs Alexandre Pinlo Alexandre.Pinlo@labri.fr LaBRI, Université Bordeax I, 351, Cors de la Libération, 33405 Talence, France Janary 17, 2006 Abstract. A homomorphism

More information