. The univariate situation. It is well-known for a long tie that denoinators of Pade approxiants can be considered as orthogonal polynoials with respe

Size: px
Start display at page:

Download ". The univariate situation. It is well-known for a long tie that denoinators of Pade approxiants can be considered as orthogonal polynoials with respe"

Transcription

1 PROPERTIES OF MULTIVARIATE HOMOGENEOUS ORTHOGONAL POLYNOMIALS Brahi Benouahane y Annie Cuyt? Keywords Abstract It is well-known that the denoinators of Pade approxiants can be considered as orthogonal polynoials with respect to a linear functional. This is usually shown by dening Pade-type approxiants fro socalled generating polynoials and then iproving the order of approxiation by iposing orthogonality conditions on the generating polynoials. In the ultivariate case, a siilar construction is possible when dealing with the ultivariate hoogeneous Pade approxiants introduced by the second author. Moreover it is shown here, that several wellknown properties of the zeroes of classical univariate orthogonal polynoials, in the case of a denite linear functional, generalize to the ultivariate hoogeneous case. For the ultivariate hoogeneous orthogonal polynoials, the absence of coon zeroes is translated to the absence of coon factors. y This research was carried out while the author was visiting the University of Antwerp as a guest researcher? Research Director FWO-Vlaanderen, Departent of atheatics and coputer science, Universiteit Antwerpen (UIA), Universiteitsplein, B{6 Wilrijk, Belgiu, eail: cuyt@uia.ua.ac.be

2 . The univariate situation. It is well-known for a long tie that denoinators of Pade approxiants can be considered as orthogonal polynoials with respect to a linear functional. This is usually shown by dening Pade-type approxiants fro so-called generating polynoials and then iproving the order of approxiation by iposing orthogonality conditions on the generating polynoials. Assue you are given a series developent f(t) By dening the linear functional c acting on the space of univariate polynoials, as c i t i f(t) can forally be rewritten as c(x i ) c i f(t) c? xt Now take any polynoial V (t) of degree and dene its associated polynoial V (x)? V (t) W (t) c x? t which is then a polynoial of degree?. Then for the Pade-type approxiation conditions ~V (t) t V (t? ) ~W (t) t? W (t? ) (f ~ V? ~ W )(t) i d i t i hold. If we do not choose V randoly, but ipose the conditions c(x i V (x)) i ; : : : ;? () then V (t) is called the orthogonal polynoial of degree with respect to the functional c (the conditions under which V can be coputed fro () are well-known [3]). For V (t) satisfying () the Pade approxiation conditions (f ~ V? ~ W )(t) hold (here V (t) is noralized such that it is onic). The Pade-type and Pade approxiants for f of degree? in the nuerator and in the denoinator are usually denoted by (? ) f and [? ] f respectively. i d i t i

3 The construction of the Pade-type and Pade approxiants ( + k) f and [ + k] f with k? explained next, follows the sae lines. The series for f(t) can be written as with If we dene the functional c by and the polynoials then W f(t) k f k (t) c i t i + t k+ f k (t) c k++i t i c (x i ) c k++i (t) c V (x)? V (t) x? t ~W (t) V ~ (t) k (f ~ V? ~ W )(t) c i t i + t k+ t? W (t? ) i+k+ and so everything reains valid with the functional c replaced by c. Note that ( + k) f W (t) ~ (t) ~V k d i t i c i t i + t k+ (? ) f k (t) The additional conditions on V necessary for the construction of the Pade approxiant [ + k] f are and we shall denote polynoials V satisfying () by V c (x i V (x)) i ; : : : ;? () so that [ + k] f ~ W V ~. The ratio W ~ V ~ which was introduced for the special case k?, will usually be denoted by W ~ () V ~ (). The sae holds for the functional c that can be denoted by c (). 3

4 . The ultivariate hoogeneous situation. In the ultivariate case, a siilar construction is possible to obtain the ultivariate hoogeneous Pade approxiants [ + k] f H introduced by Cuyt in [5]. We give a dierent and slightly ore elegant presentation than the one in [, 8, ]. We restrict our description to the bivariate case only for the reason of notational siplicity. Assue you are given a bivariate series developent f(t; s) i;j c ij t i s j For copleteness we repeat that the ultivariate hoogeneous Pade approxiant [? ] f H is dened as the irreducible for of P?; Q?; with P?; (t; s) Q?; (t; s) (fq?;? P?; ) (t; s) (?)+? i+j(?) (?)+ i+j(?) a ij t i s j b ij t i s j i+j(?)+ d ij t i s j (3) Note that the nuerator and denoinator polynoials P?; (t; s) and Q?; (t; s) start with ters of degree (? ) instead of with a constant ter. When coputing [? ] f H, in other words taking the irreducible for of P?; Q?;, the nuerator and denoinator polynoials of [? ] f H ay start with a constant ter but still this is not guaranteed. If we denote the order of the denoinator polynoial of [? ] f H (lowest hoogeneous degree of its ters) by then (? ) and we can show that the order of the nuerator polynoial of [? ] f H is at least. By dening the linear functional C acting on the space of bivariate polynoials, as i + j C(x i y j ) c ij j the bivariate series can forally be rewritten as f(t; s) C? xt? ys 4

5 By introducing the notations (t; s) ( u; u) t; s; u C ( ; ) C jjjj p C i (t; s) c i () a i () b i () d i () i j i j i j i j i j c i?j;j t i?j s j c i?j;j i?j j a i?j;j i?j j b i?j;j i?j j d i?j;j i?j j where jj:jj p is one of the Minkowski-nors on C, we can rewrite the series developent as and (3) as f(t; s) C i (t; s) c i ()u i P?; ( u; u) Q?; ( u; u) (fq?;? P?; ) ( u; u) (?)+? i(?) (?)+ i(?) i(?)+ With the introduction of the functional? acting on the variable z, as a i ()u i b i ()u i d i ()u i (4) the series can now forally also be viewed as?(z i ) c i () f(t; s) f( u; u)?? zu This new view on the ultivariate proble in which the cartesian coordinates (t; s) are replaced by the coordinates ( ; ) and u, with jjjj, will turn out to be a powerful tool in the sequel of the text. It is strongly linked to the following two features of hoogeneous ultivariate Pade approxiants: 5 (5)

6 the ost striking eleent in the denition (4) of the hoogeneous ultivariate Pade approxiant [ + k] f H is that this denition coincides with that of the univariate Pade approxiant if you discard the shift in the nuerator and denoinator degrees and replace the hoogeneous expressions by onoials [4, 6]; the hoogeneous Pade approxiants apparently satisfy a very strong projection property that we want to exploit here, reducing to univariate Pade approxiants on every straight line through the origin [6], naely [ + k] f H ( t; t) [ + k] f ; (t) with f ; (t) f( t; t) In order to clarify the presentation and underline the siilarity with the univariate case we again start with the construction of the hoogeneous Pade-type approxiants (?) f H and shall only afterwards deal with the ore general ( + k) f H. Let us rst introduce soe notations. We denote by C [u] the linear space of polynoials in the variable u with coplex coecients, by C [ ; ] the linear space of bivariate polynoials in and with coplex coecients, by C ( ; ) the coutative eld of rational functions in and with coplex coecients, by C ( ; )[u] the linear space of polynoials in the variable u with coecients fro C ( ; ) and by C [ ; ][u] the linear space of polynoials in the variable u with coecients fro C [ ; ]. For chosen and dened as above, take any function V (t; s) of the for V (t; s) V (u) B +?i() B +?i()u i +?i j b +?i?j;j +?i?j j which is a polynoial of degree in u with hoogeneous polynoial coecients fro C [ ; ] and dene V (z)? V (u) W (t; s) W (u)? z? u which is then of the for W (t; s) W (u) A +??i()???i j A +??i()u i B +??i?j()c j () Note that V (t; s) and W (t; s) do not necessarily belong to C [t; s] anyore because the hoogeneous degree in and doesn't equal the degree in u. Instead they belong to C [ ; ][u]. In the sequel of the text we will use both the notations V (t; s) and V (u) interchangeably to refer to (6a) and analogously 6 (6a) (6b)

7 for (6b). For ~V (t; s) ~ V (u) u + V (u? ) B +i()u +i +i j ~W (t; s) ~ W (u) b +i?j;jt +i?j s j u +? W (u? )?? A +i()u +i +i j a +i?j;jt +i?j s j the Pade-type approxiation conditions f V ~? W ~ (t; s) f V ~? W ~ (u) i+ i+ d i ()u i d i?j;j t i?j s j A hold, where as in (6) the subscripted function d i () is a hoogeneous function of degree i in and. We reark here that ~ V (t; s) and ~ W (t; s) again belong to C [t; s] contrary to V (t; s) and W (t; s). As in (), if the function V (t; s), say the polynoial V (u), is not chosen randoly, but if it satises the additional orthogonality conditions j?(z i V (z)) i ; : : : ;? (7) then the Pade approxiation conditions f V ~ (t; s)? W ~ (t; s) f V ~? W ~ (u) i+ i+ d i ()u i d i?j;j t i?j s j A are satised and W ~ (u)~ V (u) equals the hoogeneous Pade approxiant [? ] f H []. As in the univariate case the orthogonality conditions (7) only deterine V (u) up to a kind of noralization: 7 j

8 + polynoial coecients B +?i() ust be deterined fro conditions. How this is solved, is explained below. With the c i () we now dene the polynoial Hankel deterinants H () () c () c? ().... c (). c? () c? () H () () generalizing the classical Hankel deterinants as dened in [7]. We also call the functional? denite if H () () 6 In the sequel of the text we shall assue that V (u) satises (7) and that? is a denite functional. Also we shall assue that V (u) as given by (6a) is priitive, eaning that its polynoial coecients B +?i() are relatively prie. This last condition can always be satised, because for a denite functional? a solution of (7) is given by [] V (u) p () () c () c? () c ().... c + () c? () c? () u u V (u) (8) where the polynoial p () () is a polynoial greatest coon divisor of the polynoial coecients of the powers of u. Clearly (8) copletely deterines V (u) and consequently V (t; s). As in the univariate situation the functional? can be dened by? (z i ) c k++i () and? can be replaced by? for the construction of hoogeneous Pade approxiants [ + k] f H with k?. The shift in the nuerator and denoinator degrees of [ + k] f H then satises ( + k) and the nuerator and denoinator of [+k] f H are respectively denoted by W ~ (t; s) W ~ (u) and V ~ (t; s) V ~ (u). We denote by p () a polynoial greatest coon divisor of the polynoial coecients of u i ; i ; : : : ; in the deterinant c k+ () c k+ () c k++ ().... c k++ () c k+ () c k+ () u u 8

9 and identify W V and? respectively with W () V () and? (). It is then easy to check that for V given by V (u) p () c k+ () c k+ () c k++ ().... c k++ () c k+ () c k+ () u u V (u) (9) one has? u V (u)? p () p () H + () p () c k+ () c k+ () c k++ ().... c k++ () c k+ () c k+ () u u + u c k+ () c k+ () c k++ ()..... c k+ () c k+ () c k++ () c k++ () c k++ () C A () To conclude this section we suarize the ost iportant results. Suary: (a) For the bivariate series f(t; s) and for k? holds [ + k] f H (t; s) ~ W (t; s) ~V (t; s) (b) For the onic univariate polynoial V (u) satisfying () and for the bivariate polynoial V (t; s) V (u) given by (8) with (t; s) ( u; u) holds H () ( ; )V (u) p () ( ; )V ( u; u) p () ( ; )V (u) This last property can be seen as a projection property. 9

10 3. Properties of the hoogeneous orthogonal polynoials. Let us now generalize the well-known univariate property [3, p. 57] that for a denite functional c as in () the polynoials V (t) and V + (t) have no coon zeroes. The sae is true in the univariate case for the polynoials W (t) and W + (t), and the polynoials V (t) and W (t). Before we can forulate the ultivariate generalization, we rst need a nuber of leas and theores. In the ultivariate discussion we shall often switch between the coordinates (t; s) and the coordinate u in the one-diensional subspaces spanned by the vectors. Reeber that V (t; s) V (u) and W (t; s) W (u) do not belong to C [t; s] but to C [ ; ][u]. Lea : Let the functional? which is dened for k? be denite and let the polynoials fv (u)g satisfy (7). Then the fv (u)g are linearly independent in C ( ; )[u]. Proof: Suppose we have coecients (); (); : : : C ( ; ) such that 8u C : i ()V i (u) Then we also have for j that i ()? u j V i (u) Taking (7) into account, we obtain for j For j this reduces to j i ()? u j V i (u) ()? V (u) which results in () because? V (u) that j () is by induction. Theore : Let the functional? and p recurrence relations c k+ () H () 6. For j > the proof which is dened for k? be denite and let the polynoials V (u) (u)g and fw (u)g satisfy the () be dened as in (9). Then the polynoials fv V + (t; s) + () W + (t; s) (u? + ())V V? (t; s) V (t; s) + () (u? + ())W W? (t; s)? W (t; s) (t; s)? + ()V? (t; s) (t; s)? + ()W? (t; s)

11 with + p () H () p + () + ()? u + () () h V (t; s) H? hv (t; s) i i +? () () p p () H + () H () () c k+ () Proof: The polynoial uv (u) uv (t; s) as dened in (6a) can be written as a linear cobination where the i V j + uv (t; s) i ()V i (t; s) () are rational functions of the variable. We ultiply left and right hand side with (t; s) and apply the linear functional? to obtain On the other hand we have so that consequently i () i ; : : : ;?? ()? () Using () and the fact that + ()? V uv? (t; s)v (t; s)? (V? (t; + s)) (t; s))? u(v? (V uv (t; s)) (t; s)v + (t; s) + ()? (V + (t; s)) (u) V H () p ()? (V (u)) (t; s) H () p () u + : : : + () H H () + () p + () p ()? u V (u)

12 the expression for + () is obtained. For the associated polynoials W (u) we have, because? V (z), W + (u) + ()? (u? + ())V (u)? V (z) u? z? + which gives the desired result. The starting value for () is easy to verify. p? ()V (u)? V? (z) u? z Theore : Let the functional? which is dened for k? be denite and let the polynoials V () be dened as in (9). Then the polynoials fv (u)g and fw V (u)w + (u)? W (u)v + (u) V (t; s)w h H + () i + p ()p + () Proof: For siplicity we oit writing the arguents (t; s) in V. The proof akes use of the previous recurrence relations: W V + + V W + + By subtracting these expressions one obtains V W +? W (u? + (u? + V : : : h H + i p p + and W (t; s)? W (u) and (u)g satisfy the identity (t; s)v + (t; s) and () in ; and )V W? + V? W )W V? + W? V V W? W V Let us now take a closer look at the factorisation of the orthogonal polynoials V (u) and their associated polynoials W (u) in irreducible factors. This factorisation is unique in C [ ; ][u] except for ultiplicative constants fro C which are the unit ultiples in C [ ; ] and except for the order of the factors. This is because C [ ; ][u] is a unique factorization doain. Theore 3: Let the functional? which is dened for k? be denite and let the polynoials V () be dened as in (9). Let W (u) be given by (6b). Then p (a) V (b) W (c) V (u) and V + (u) and W + (u) and W (u) have no coon factor (u) have no coon factor (u) have no coon factor (u) and Proof: We only give the proof for (a) since the proof for (b) and (c) is copletely siilar. The proof is by!

13 contradiction. Assue that V (u) and V + (u) have a coon factor. Then, because of theore, it is necessarily a polynoial in, dierent fro a coplex constant if it is a true coon factor. Hence the polynoials V (u) and V + (u) are not priitive, which is a contradiction. Let us now restrict ourselves to all variables and coecients being real and turn to soe results for positive denite functionals. The functional? is called positive denite if 8 IR : H () > Lea : For a positive denite functional? and for any polynoial P(u) IR[ ; ][u] holds?? P (u) > where the functional? acts on the variable u as dened above. Proof: Every polynoial P(u) of degree in IR[ ; ][u] can be written in the for P(u) i ()V i (u) where the i () IR( ; ) are rational functions of the variable with real coecients. Fro the orthogonality conditions satised by V (u) we obtain?? P (u) i ()? (V i (u)) i () H j ()H j+ () p j > Theore 4: For a positive denite functional?, the polynoials V factors in IR[ ; ][u] of ultiplicity larger than. () (u) satisfying (7) have no irreducible Proof: Assue V (u) has an irreducible factor F(u) of ultiplicity ` >. Then we can write V (u) F `(u)z(u) where Z(u) is a polynoial in u of u F < u F is the degree of F(u) as a polynoial in u. If ` > is even then because of lea? Z(u)V (u)?? Z (u)f `(u) which is ipossible because of the orthogonality conditions satised by V. If ` > is odd then which is also a contradiction.? F(u)Z(u)V (u) >?? Z (u)f `+ (u) > 3

14 4. Coon zeroes instead of coon factors. Fro the previous section it is clear that our orthogonal polynoials fv (u)g IN do not have any irreducible factors in coon in C [ ; ][u]. Since each of these irreducible factors uniquely deterines a zero curve, it is also clear that the fv (t; s)g IN do not have any zero curves in coon. But since their coecients belong to the unique factorization doain C [ ; ], we can use a well-known theore to detect isolated zeroes for which for instance V vanish siultaneously. (u) V (t; s) and V n Lea 3: Let the functional? which is dened for k? be denite. Let the polynoials satisfy (7). Then V R() V (u) v i ()u i (u) and V n (u) have a coon zero for ( ; ) satisfying () : : : v () v () : : : v () n () : : : v nn () v n () : : : v nn () v v 9 > >; n ties 9 > >; ties (u) V n (t; s) Proof: The (n + ) (n + ) deterinant R() is the resultant of the polynoials V (u) and V n (u) and this proves the lea [9, pp. 3{3]. We can illustrate this procedure with a siple exaple. Consider the functional The orthogonal polynoials V () V () (u)? ( + ) + u? () (z i ) c i () i! (i + i? + : : : + i ) () (u) and V (u) satisfying (7) are then given by V () (u)? ( )+ + 6 ( )u? ( )u The resultant of V () () (u) and V (u) equals R()? 64 (3 + p 5) + (3? p 5) + 4

15 Consequently V () (t; s) V () () (u) and V (t; s) V () (u) have a coon zero for satisfying ( R() This is for and or in ters of t and s, for and () 3 jjjj s s s p 5 ; s 6 3? p 5 ; 3 + p 5A 6 3? p 5A 6 (t; s) (t () ; s () )? + p p 5 ; + p 5 6 (t; s) (t () ; s () )?? p 5 9? 3 p 5 ;? p 5 6!! Let us at the sae tie illustrate that W ~ () (u) V ~ () (u) W ~ () (t; s) V ~ () (t; s) equals the hoogeneous Pade approxiant [] f H for the series f(t; s) Fro V () () (u) V (t; s) we copute ~V () (t; s) u 4 ~ V () (u? ) c i ()u i t exp(t)? s exp(s) t? s i;j? (t4 + t 3 s + 5t s + ts 3 + s 4 )+ (i + j)! ti s j + 6 (t3 + 5t s + 5ts + s 3 )? (t + 3ts + s ) and (t; s)? V () () (z)? V (u) z? u W () ~W () (t; s) u 3 W () (u? )!? (t + 3ts + s )? 6 (t3 + 7t s + 7ts + s 3 ) to obtain [] f H. 5

16 References [] S. Arioka. Pade-type approxiants in ultivariables. Appl. Nuer. Math., 3:497{5, 987. [] B. Benouahane. Approxiants de Pade \hoogenes" et polyn^oes orthogonaux a deux variables. Rend. Mat. (7), :673{689, 99. [3] C. Brezinski. Pade type approxiation and general orthogonal polynoials. ISNM 5, Birkhauser Verlag, Basel, 98. [4] A. Cuyt. A coparison of soe ultivariate Pade approxiants. SIAM J. Math. Anal., 4:95{, 983. [5] A. Cuyt. Pade approxiants for operators: theory and applications. LNM 65, Springer Verlag, Berlin, 984. [6] A. Cuyt. How well can the concept of Pade approxiant be generalized to the ultivariate case? J. Coput. Appl. Math., 5:5{5, 999. [7] P. Henrici. Applied and coputational coplex analysis I. John Wiley, New York, 974. [8] S. Kida. Pade-type and Pade approxiants in several variables. Appl. Nuer. Math., 6:37{39, 89/9. [9] R.J. Walker. Algebraic Curves. Dover Publications, New York, 95. 6

Chapter 6 1-D Continuous Groups

Chapter 6 1-D Continuous Groups Chapter 6 1-D Continuous Groups Continuous groups consist of group eleents labelled by one or ore continuous variables, say a 1, a 2,, a r, where each variable has a well- defined range. This chapter explores:

More information

List Scheduling and LPT Oliver Braun (09/05/2017)

List Scheduling and LPT Oliver Braun (09/05/2017) List Scheduling and LPT Oliver Braun (09/05/207) We investigate the classical scheduling proble P ax where a set of n independent jobs has to be processed on 2 parallel and identical processors (achines)

More information

Analysis of Polynomial & Rational Functions ( summary )

Analysis of Polynomial & Rational Functions ( summary ) Analysis of Polynoial & Rational Functions ( suary ) The standard for of a polynoial function is ( ) where each of the nubers are called the coefficients. The polynoial of is said to have degree n, where

More information

arxiv: v1 [math.nt] 14 Sep 2014

arxiv: v1 [math.nt] 14 Sep 2014 ROTATION REMAINDERS P. JAMESON GRABER, WASHINGTON AND LEE UNIVERSITY 08 arxiv:1409.411v1 [ath.nt] 14 Sep 014 Abstract. We study properties of an array of nubers, called the triangle, in which each row

More information

A1. Find all ordered pairs (a, b) of positive integers for which 1 a + 1 b = 3

A1. Find all ordered pairs (a, b) of positive integers for which 1 a + 1 b = 3 A. Find all ordered pairs a, b) of positive integers for which a + b = 3 08. Answer. The six ordered pairs are 009, 08), 08, 009), 009 337, 674) = 35043, 674), 009 346, 673) = 3584, 673), 674, 009 337)

More information

a a a a a a a m a b a b

a a a a a a a m a b a b Algebra / Trig Final Exa Study Guide (Fall Seester) Moncada/Dunphy Inforation About the Final Exa The final exa is cuulative, covering Appendix A (A.1-A.5) and Chapter 1. All probles will be ultiple choice

More information

THE POLYNOMIAL REPRESENTATION OF THE TYPE A n 1 RATIONAL CHEREDNIK ALGEBRA IN CHARACTERISTIC p n

THE POLYNOMIAL REPRESENTATION OF THE TYPE A n 1 RATIONAL CHEREDNIK ALGEBRA IN CHARACTERISTIC p n THE POLYNOMIAL REPRESENTATION OF THE TYPE A n RATIONAL CHEREDNIK ALGEBRA IN CHARACTERISTIC p n SHEELA DEVADAS AND YI SUN Abstract. We study the polynoial representation of the rational Cherednik algebra

More information

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices CS71 Randoness & Coputation Spring 018 Instructor: Alistair Sinclair Lecture 13: February 7 Disclaier: These notes have not been subjected to the usual scrutiny accorded to foral publications. They ay

More information

G G G G G. Spec k G. G Spec k G G. G G m G. G Spec k. Spec k

G G G G G. Spec k G. G Spec k G G. G G m G. G Spec k. Spec k 12 VICTORIA HOSKINS 3. Algebraic group actions and quotients In this section we consider group actions on algebraic varieties and also describe what type of quotients we would like to have for such group

More information

New upper bound for the B-spline basis condition number II. K. Scherer. Institut fur Angewandte Mathematik, Universitat Bonn, Bonn, Germany.

New upper bound for the B-spline basis condition number II. K. Scherer. Institut fur Angewandte Mathematik, Universitat Bonn, Bonn, Germany. New upper bound for the B-spline basis condition nuber II. A proof of de Boor's 2 -conjecture K. Scherer Institut fur Angewandte Matheati, Universitat Bonn, 535 Bonn, Gerany and A. Yu. Shadrin Coputing

More information

Curious Bounds for Floor Function Sums

Curious Bounds for Floor Function Sums 1 47 6 11 Journal of Integer Sequences, Vol. 1 (018), Article 18.1.8 Curious Bounds for Floor Function Sus Thotsaporn Thanatipanonda and Elaine Wong 1 Science Division Mahidol University International

More information

Feature Extraction Techniques

Feature Extraction Techniques Feature Extraction Techniques Unsupervised Learning II Feature Extraction Unsupervised ethods can also be used to find features which can be useful for categorization. There are unsupervised ethods that

More information

i ij j ( ) sin cos x y z x x x interchangeably.)

i ij j ( ) sin cos x y z x x x interchangeably.) Tensor Operators Michael Fowler,2/3/12 Introduction: Cartesian Vectors and Tensors Physics is full of vectors: x, L, S and so on Classically, a (three-diensional) vector is defined by its properties under

More information

Generalized eigenfunctions and a Borel Theorem on the Sierpinski Gasket.

Generalized eigenfunctions and a Borel Theorem on the Sierpinski Gasket. Generalized eigenfunctions and a Borel Theore on the Sierpinski Gasket. Kasso A. Okoudjou, Luke G. Rogers, and Robert S. Strichartz May 26, 2006 1 Introduction There is a well developed theory (see [5,

More information

EXPLICIT CONGRUENCES FOR EULER POLYNOMIALS

EXPLICIT CONGRUENCES FOR EULER POLYNOMIALS EXPLICIT CONGRUENCES FOR EULER POLYNOMIALS Zhi-Wei Sun Departent of Matheatics, Nanjing University Nanjing 10093, People s Republic of China zwsun@nju.edu.cn Abstract In this paper we establish soe explicit

More information

CSE525: Randomized Algorithms and Probabilistic Analysis May 16, Lecture 13

CSE525: Randomized Algorithms and Probabilistic Analysis May 16, Lecture 13 CSE55: Randoied Algoriths and obabilistic Analysis May 6, Lecture Lecturer: Anna Karlin Scribe: Noah Siegel, Jonathan Shi Rando walks and Markov chains This lecture discusses Markov chains, which capture

More information

A note on the multiplication of sparse matrices

A note on the multiplication of sparse matrices Cent. Eur. J. Cop. Sci. 41) 2014 1-11 DOI: 10.2478/s13537-014-0201-x Central European Journal of Coputer Science A note on the ultiplication of sparse atrices Research Article Keivan Borna 12, Sohrab Aboozarkhani

More information

RESTARTED FULL ORTHOGONALIZATION METHOD FOR SHIFTED LINEAR SYSTEMS

RESTARTED FULL ORTHOGONALIZATION METHOD FOR SHIFTED LINEAR SYSTEMS BIT Nuerical Matheatics 43: 459 466, 2003. 2003 Kluwer Acadeic Publishers. Printed in The Netherlands 459 RESTARTED FULL ORTHOGONALIZATION METHOD FOR SHIFTED LINEAR SYSTEMS V. SIMONCINI Dipartiento di

More information

SERIES, AND ATKIN S ORTHOGONAL POLYNOMIALS. M. Kaneko and D. Zagier

SERIES, AND ATKIN S ORTHOGONAL POLYNOMIALS. M. Kaneko and D. Zagier SUPERSINGULAR j-invariants, HYPERGEOMETRIC SERIES, AND ATKIN S ORTHOGONAL POLYNOMIALS M. Kaneko and D. Zagier 1. Introduction. An elliptic curve E over a field K of characteristic p > 0 is called supersingular

More information

Fast Montgomery-like Square Root Computation over GF(2 m ) for All Trinomials

Fast Montgomery-like Square Root Computation over GF(2 m ) for All Trinomials Fast Montgoery-like Square Root Coputation over GF( ) for All Trinoials Yin Li a, Yu Zhang a, a Departent of Coputer Science and Technology, Xinyang Noral University, Henan, P.R.China Abstract This letter

More information

Characterization of the Line Complexity of Cellular Automata Generated by Polynomial Transition Rules. Bertrand Stone

Characterization of the Line Complexity of Cellular Automata Generated by Polynomial Transition Rules. Bertrand Stone Characterization of the Line Coplexity of Cellular Autoata Generated by Polynoial Transition Rules Bertrand Stone Abstract Cellular autoata are discrete dynaical systes which consist of changing patterns

More information

arxiv: v2 [math.nt] 5 Sep 2012

arxiv: v2 [math.nt] 5 Sep 2012 ON STRONGER CONJECTURES THAT IMPLY THE ERDŐS-MOSER CONJECTURE BERND C. KELLNER arxiv:1003.1646v2 [ath.nt] 5 Sep 2012 Abstract. The Erdős-Moser conjecture states that the Diophantine equation S k () = k,

More information

Using EM To Estimate A Probablity Density With A Mixture Of Gaussians

Using EM To Estimate A Probablity Density With A Mixture Of Gaussians Using EM To Estiate A Probablity Density With A Mixture Of Gaussians Aaron A. D Souza adsouza@usc.edu Introduction The proble we are trying to address in this note is siple. Given a set of data points

More information

Algebraic Montgomery-Yang problem: the log del Pezzo surface case

Algebraic Montgomery-Yang problem: the log del Pezzo surface case c 2014 The Matheatical Society of Japan J. Math. Soc. Japan Vol. 66, No. 4 (2014) pp. 1073 1089 doi: 10.2969/jsj/06641073 Algebraic Montgoery-Yang proble: the log del Pezzo surface case By DongSeon Hwang

More information

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science A Better Algorith For an Ancient Scheduling Proble David R. Karger Steven J. Phillips Eric Torng Departent of Coputer Science Stanford University Stanford, CA 9435-4 Abstract One of the oldest and siplest

More information

Solutions of some selected problems of Homework 4

Solutions of some selected problems of Homework 4 Solutions of soe selected probles of Hoework 4 Sangchul Lee May 7, 2018 Proble 1 Let there be light A professor has two light bulbs in his garage. When both are burned out, they are replaced, and the next

More information

The Weierstrass Approximation Theorem

The Weierstrass Approximation Theorem 36 The Weierstrass Approxiation Theore Recall that the fundaental idea underlying the construction of the real nubers is approxiation by the sipler rational nubers. Firstly, nubers are often deterined

More information

Soft Computing Techniques Help Assign Weights to Different Factors in Vulnerability Analysis

Soft Computing Techniques Help Assign Weights to Different Factors in Vulnerability Analysis Soft Coputing Techniques Help Assign Weights to Different Factors in Vulnerability Analysis Beverly Rivera 1,2, Irbis Gallegos 1, and Vladik Kreinovich 2 1 Regional Cyber and Energy Security Center RCES

More information

ORIGAMI CONSTRUCTIONS OF RINGS OF INTEGERS OF IMAGINARY QUADRATIC FIELDS

ORIGAMI CONSTRUCTIONS OF RINGS OF INTEGERS OF IMAGINARY QUADRATIC FIELDS #A34 INTEGERS 17 (017) ORIGAMI CONSTRUCTIONS OF RINGS OF INTEGERS OF IMAGINARY QUADRATIC FIELDS Jürgen Kritschgau Departent of Matheatics, Iowa State University, Aes, Iowa jkritsch@iastateedu Adriana Salerno

More information

On Certain C-Test Words for Free Groups

On Certain C-Test Words for Free Groups Journal of Algebra 247, 509 540 2002 doi:10.1006 jabr.2001.9001, available online at http: www.idealibrary.co on On Certain C-Test Words for Free Groups Donghi Lee Departent of Matheatics, Uni ersity of

More information

A Bernstein-Markov Theorem for Normed Spaces

A Bernstein-Markov Theorem for Normed Spaces A Bernstein-Markov Theore for Nored Spaces Lawrence A. Harris Departent of Matheatics, University of Kentucky Lexington, Kentucky 40506-0027 Abstract Let X and Y be real nored linear spaces and let φ :

More information

3.8 Three Types of Convergence

3.8 Three Types of Convergence 3.8 Three Types of Convergence 3.8 Three Types of Convergence 93 Suppose that we are given a sequence functions {f k } k N on a set X and another function f on X. What does it ean for f k to converge to

More information

Singularities of divisors on abelian varieties

Singularities of divisors on abelian varieties Singularities of divisors on abelian varieties Olivier Debarre March 20, 2006 This is joint work with Christopher Hacon. We work over the coplex nubers. Let D be an effective divisor on an abelian variety

More information

ALGEBRA REVIEW. MULTINOMIAL An algebraic expression consisting of more than one term.

ALGEBRA REVIEW. MULTINOMIAL An algebraic expression consisting of more than one term. Page 1 of 6 ALGEBRAIC EXPRESSION A cobination of ordinary nubers, letter sybols, variables, grouping sybols and operation sybols. Nubers reain fixed in value and are referred to as constants. Letter sybols

More information

Block designs and statistics

Block designs and statistics Bloc designs and statistics Notes for Math 447 May 3, 2011 The ain paraeters of a bloc design are nuber of varieties v, bloc size, nuber of blocs b. A design is built on a set of v eleents. Each eleent

More information

Probability Distributions

Probability Distributions Probability Distributions In Chapter, we ephasized the central role played by probability theory in the solution of pattern recognition probles. We turn now to an exploration of soe particular exaples

More information

M ath. Res. Lett. 15 (2008), no. 2, c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS. Van H. Vu. 1.

M ath. Res. Lett. 15 (2008), no. 2, c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS. Van H. Vu. 1. M ath. Res. Lett. 15 (2008), no. 2, 375 388 c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS Van H. Vu Abstract. Let F q be a finite field of order q and P be a polynoial in F q[x

More information

The Fundamental Basis Theorem of Geometry from an algebraic point of view

The Fundamental Basis Theorem of Geometry from an algebraic point of view Journal of Physics: Conference Series PAPER OPEN ACCESS The Fundaental Basis Theore of Geoetry fro an algebraic point of view To cite this article: U Bekbaev 2017 J Phys: Conf Ser 819 012013 View the article

More information

Polygonal Designs: Existence and Construction

Polygonal Designs: Existence and Construction Polygonal Designs: Existence and Construction John Hegean Departent of Matheatics, Stanford University, Stanford, CA 9405 Jeff Langford Departent of Matheatics, Drake University, Des Moines, IA 5011 G

More information

Tight Bounds for Maximal Identifiability of Failure Nodes in Boolean Network Tomography

Tight Bounds for Maximal Identifiability of Failure Nodes in Boolean Network Tomography Tight Bounds for axial Identifiability of Failure Nodes in Boolean Network Toography Nicola Galesi Sapienza Università di Roa nicola.galesi@uniroa1.it Fariba Ranjbar Sapienza Università di Roa fariba.ranjbar@uniroa1.it

More information

THE AVERAGE NORM OF POLYNOMIALS OF FIXED HEIGHT

THE AVERAGE NORM OF POLYNOMIALS OF FIXED HEIGHT THE AVERAGE NORM OF POLYNOMIALS OF FIXED HEIGHT PETER BORWEIN AND KWOK-KWONG STEPHEN CHOI Abstract. Let n be any integer and ( n ) X F n : a i z i : a i, ± i be the set of all polynoials of height and

More information

A Markov Framework for the Simple Genetic Algorithm

A Markov Framework for the Simple Genetic Algorithm A arkov Fraework for the Siple Genetic Algorith Thoas E. Davis*, Jose C. Principe Electrical Engineering Departent University of Florida, Gainesville, FL 326 *WL/NGS Eglin AFB, FL32542 Abstract This paper

More information

lecture 36: Linear Multistep Mehods: Zero Stability

lecture 36: Linear Multistep Mehods: Zero Stability 95 lecture 36: Linear Multistep Mehods: Zero Stability 5.6 Linear ultistep ethods: zero stability Does consistency iply convergence for linear ultistep ethods? This is always the case for one-step ethods,

More information

1 Bounding the Margin

1 Bounding the Margin COS 511: Theoretical Machine Learning Lecturer: Rob Schapire Lecture #12 Scribe: Jian Min Si March 14, 2013 1 Bounding the Margin We are continuing the proof of a bound on the generalization error of AdaBoost

More information

Closed-form evaluations of Fibonacci Lucas reciprocal sums with three factors

Closed-form evaluations of Fibonacci Lucas reciprocal sums with three factors Notes on Nuber Theory Discrete Matheatics Print ISSN 30-32 Online ISSN 2367-827 Vol. 23 207 No. 2 04 6 Closed-for evaluations of Fibonacci Lucas reciprocal sus with three factors Robert Frontczak Lesbank

More information

SINGULAR POLYNOMIALS FOR THE SYMMETRIC GROUPS

SINGULAR POLYNOMIALS FOR THE SYMMETRIC GROUPS SINGULAR POLYNOMIALS FOR THE SYMMETRIC GROUPS CHARLES F. DUNKL Abstract. For certain negative rational nubers 0, called singular values, and associated with the syetric group S N on N objects, there exist

More information

A Note on Online Scheduling for Jobs with Arbitrary Release Times

A Note on Online Scheduling for Jobs with Arbitrary Release Times A Note on Online Scheduling for Jobs with Arbitrary Release Ties Jihuan Ding, and Guochuan Zhang College of Operations Research and Manageent Science, Qufu Noral University, Rizhao 7686, China dingjihuan@hotail.co

More information

Lecture 21. Interior Point Methods Setup and Algorithm

Lecture 21. Interior Point Methods Setup and Algorithm Lecture 21 Interior Point Methods In 1984, Kararkar introduced a new weakly polynoial tie algorith for solving LPs [Kar84a], [Kar84b]. His algorith was theoretically faster than the ellipsoid ethod and

More information

arxiv:math/ v1 [math.nt] 15 Jul 2003

arxiv:math/ v1 [math.nt] 15 Jul 2003 arxiv:ath/0307203v [ath.nt] 5 Jul 2003 A quantitative version of the Roth-Ridout theore Toohiro Yaada, 606-8502, Faculty of Science, Kyoto University, Kitashirakawaoiwakecho, Sakyoku, Kyoto-City, Kyoto,

More information

MULTIPLAYER ROCK-PAPER-SCISSORS

MULTIPLAYER ROCK-PAPER-SCISSORS MULTIPLAYER ROCK-PAPER-SCISSORS CHARLOTTE ATEN Contents 1. Introduction 1 2. RPS Magas 3 3. Ites as a Function of Players and Vice Versa 5 4. Algebraic Properties of RPS Magas 6 References 6 1. Introduction

More information

1. INTRODUCTION AND RESULTS

1. INTRODUCTION AND RESULTS SOME IDENTITIES INVOLVING THE FIBONACCI NUMBERS AND LUCAS NUMBERS Wenpeng Zhang Research Center for Basic Science, Xi an Jiaotong University Xi an Shaanxi, People s Republic of China (Subitted August 00

More information

The Methods of Solution for Constrained Nonlinear Programming

The Methods of Solution for Constrained Nonlinear Programming Research Inventy: International Journal Of Engineering And Science Vol.4, Issue 3(March 2014), PP 01-06 Issn (e): 2278-4721, Issn (p):2319-6483, www.researchinventy.co The Methods of Solution for Constrained

More information

A Simple Regression Problem

A Simple Regression Problem A Siple Regression Proble R. M. Castro March 23, 2 In this brief note a siple regression proble will be introduced, illustrating clearly the bias-variance tradeoff. Let Y i f(x i ) + W i, i,..., n, where

More information

Algorithms for parallel processor scheduling with distinct due windows and unit-time jobs

Algorithms for parallel processor scheduling with distinct due windows and unit-time jobs BULLETIN OF THE POLISH ACADEMY OF SCIENCES TECHNICAL SCIENCES Vol. 57, No. 3, 2009 Algoriths for parallel processor scheduling with distinct due windows and unit-tie obs A. JANIAK 1, W.A. JANIAK 2, and

More information

On Poset Merging. 1 Introduction. Peter Chen Guoli Ding Steve Seiden. Keywords: Merging, Partial Order, Lower Bounds. AMS Classification: 68W40

On Poset Merging. 1 Introduction. Peter Chen Guoli Ding Steve Seiden. Keywords: Merging, Partial Order, Lower Bounds. AMS Classification: 68W40 On Poset Merging Peter Chen Guoli Ding Steve Seiden Abstract We consider the follow poset erging proble: Let X and Y be two subsets of a partially ordered set S. Given coplete inforation about the ordering

More information

A Generalized Permanent Estimator and its Application in Computing Multi- Homogeneous Bézout Number

A Generalized Permanent Estimator and its Application in Computing Multi- Homogeneous Bézout Number Research Journal of Applied Sciences, Engineering and Technology 4(23): 5206-52, 202 ISSN: 2040-7467 Maxwell Scientific Organization, 202 Subitted: April 25, 202 Accepted: May 3, 202 Published: Deceber

More information

MA304 Differential Geometry

MA304 Differential Geometry MA304 Differential Geoetry Hoework 4 solutions Spring 018 6% of the final ark 1. The paraeterised curve αt = t cosh t for t R is called the catenary. Find the curvature of αt. Solution. Fro hoework question

More information

Bernoulli numbers and generalized factorial sums

Bernoulli numbers and generalized factorial sums Bernoulli nubers and generalized factorial sus Paul Thoas Young Departent of Matheatics, College of Charleston Charleston, SC 29424 paul@ath.cofc.edu June 25, 2010 Abstract We prove a pair of identities

More information

Finite fields. and we ve used it in various examples and homework problems. In these notes I will introduce more finite fields

Finite fields. and we ve used it in various examples and homework problems. In these notes I will introduce more finite fields Finite fields I talked in class about the field with two eleents F 2 = {, } and we ve used it in various eaples and hoework probles. In these notes I will introduce ore finite fields F p = {,,...,p } for

More information

time time δ jobs jobs

time time δ jobs jobs Approxiating Total Flow Tie on Parallel Machines Stefano Leonardi Danny Raz y Abstract We consider the proble of optiizing the total ow tie of a strea of jobs that are released over tie in a ultiprocessor

More information

The Hilbert Schmidt version of the commutator theorem for zero trace matrices

The Hilbert Schmidt version of the commutator theorem for zero trace matrices The Hilbert Schidt version of the coutator theore for zero trace atrices Oer Angel Gideon Schechtan March 205 Abstract Let A be a coplex atrix with zero trace. Then there are atrices B and C such that

More information

The accelerated expansion of the universe is explained by quantum field theory.

The accelerated expansion of the universe is explained by quantum field theory. The accelerated expansion of the universe is explained by quantu field theory. Abstract. Forulas describing interactions, in fact, use the liiting speed of inforation transfer, and not the speed of light.

More information

Perturbation on Polynomials

Perturbation on Polynomials Perturbation on Polynoials Isaila Diouf 1, Babacar Diakhaté 1 & Abdoul O Watt 2 1 Départeent Maths-Infos, Université Cheikh Anta Diop, Dakar, Senegal Journal of Matheatics Research; Vol 5, No 3; 2013 ISSN

More information

APPROXIMATION BY MODIFIED SZÁSZ-MIRAKYAN OPERATORS

APPROXIMATION BY MODIFIED SZÁSZ-MIRAKYAN OPERATORS APPROXIMATION BY MODIFIED SZÁSZ-MIRAKYAN OPERATORS Received: 23 Deceber, 2008 Accepted: 28 May, 2009 Counicated by: L. REMPULSKA AND S. GRACZYK Institute of Matheatics Poznan University of Technology ul.

More information

On the Inapproximability of Vertex Cover on k-partite k-uniform Hypergraphs

On the Inapproximability of Vertex Cover on k-partite k-uniform Hypergraphs On the Inapproxiability of Vertex Cover on k-partite k-unifor Hypergraphs Venkatesan Guruswai and Rishi Saket Coputer Science Departent Carnegie Mellon University Pittsburgh, PA 1513. Abstract. Coputing

More information

arxiv: v1 [math.gr] 18 Dec 2017

arxiv: v1 [math.gr] 18 Dec 2017 Probabilistic aspects of ZM-groups arxiv:7206692v [athgr] 8 Dec 207 Mihai-Silviu Lazorec Deceber 7, 207 Abstract In this paper we study probabilistic aspects such as (cyclic) subgroup coutativity degree

More information

Holomorphic curves into algebraic varieties

Holomorphic curves into algebraic varieties Annals of Matheatics, 69 29, 255 267 Holoorphic curves into algebraic varieties By Min Ru* Abstract This paper establishes a defect relation for algebraically nondegenerate holoorphic appings into an arbitrary

More information

Uniform Approximation and Bernstein Polynomials with Coefficients in the Unit Interval

Uniform Approximation and Bernstein Polynomials with Coefficients in the Unit Interval Unifor Approxiation and Bernstein Polynoials with Coefficients in the Unit Interval Weiang Qian and Marc D. Riedel Electrical and Coputer Engineering, University of Minnesota 200 Union St. S.E. Minneapolis,

More information

Linear recurrences and asymptotic behavior of exponential sums of symmetric boolean functions

Linear recurrences and asymptotic behavior of exponential sums of symmetric boolean functions Linear recurrences and asyptotic behavior of exponential sus of syetric boolean functions Francis N. Castro Departent of Matheatics University of Puerto Rico, San Juan, PR 00931 francis.castro@upr.edu

More information

Non-Parametric Non-Line-of-Sight Identification 1

Non-Parametric Non-Line-of-Sight Identification 1 Non-Paraetric Non-Line-of-Sight Identification Sinan Gezici, Hisashi Kobayashi and H. Vincent Poor Departent of Electrical Engineering School of Engineering and Applied Science Princeton University, Princeton,

More information

DERIVING PROPER UNIFORM PRIORS FOR REGRESSION COEFFICIENTS

DERIVING PROPER UNIFORM PRIORS FOR REGRESSION COEFFICIENTS DERIVING PROPER UNIFORM PRIORS FOR REGRESSION COEFFICIENTS N. van Erp and P. van Gelder Structural Hydraulic and Probabilistic Design, TU Delft Delft, The Netherlands Abstract. In probles of odel coparison

More information

Convex Programming for Scheduling Unrelated Parallel Machines

Convex Programming for Scheduling Unrelated Parallel Machines Convex Prograing for Scheduling Unrelated Parallel Machines Yossi Azar Air Epstein Abstract We consider the classical proble of scheduling parallel unrelated achines. Each job is to be processed by exactly

More information

Linear Transformations

Linear Transformations Linear Transforations Hopfield Network Questions Initial Condition Recurrent Layer p S x W S x S b n(t + ) a(t + ) S x S x D a(t) S x S S x S a(0) p a(t + ) satlins (Wa(t) + b) The network output is repeatedly

More information

NORMAL MATRIX POLYNOMIALS WITH NONSINGULAR LEADING COEFFICIENTS

NORMAL MATRIX POLYNOMIALS WITH NONSINGULAR LEADING COEFFICIENTS NORMAL MATRIX POLYNOMIALS WITH NONSINGULAR LEADING COEFFICIENTS NIKOLAOS PAPATHANASIOU AND PANAYIOTIS PSARRAKOS Abstract. In this paper, we introduce the notions of weakly noral and noral atrix polynoials,

More information

Physics 215 Winter The Density Matrix

Physics 215 Winter The Density Matrix Physics 215 Winter 2018 The Density Matrix The quantu space of states is a Hilbert space H. Any state vector ψ H is a pure state. Since any linear cobination of eleents of H are also an eleent of H, it

More information

m-fold Hypergeometric Solutions of Linear Recurrence Equations Revisited

m-fold Hypergeometric Solutions of Linear Recurrence Equations Revisited -fold Hypergeoetric Solutions of Linear Recurrence Equations Revisited Peter Horn, Wolfra Koepf, Torsten Sprenger Institute of Matheatics, University of Kassel, D-34132 Kassel, Gerany Abstract We present

More information

Explicit solution of the polynomial least-squares approximation problem on Chebyshev extrema nodes

Explicit solution of the polynomial least-squares approximation problem on Chebyshev extrema nodes Explicit solution of the polynoial least-squares approxiation proble on Chebyshev extrea nodes Alfredo Eisinberg, Giuseppe Fedele Dipartiento di Elettronica Inforatica e Sisteistica, Università degli Studi

More information

Physics 139B Solutions to Homework Set 3 Fall 2009

Physics 139B Solutions to Homework Set 3 Fall 2009 Physics 139B Solutions to Hoework Set 3 Fall 009 1. Consider a particle of ass attached to a rigid assless rod of fixed length R whose other end is fixed at the origin. The rod is free to rotate about

More information

Divisibility of Polynomials over Finite Fields and Combinatorial Applications

Divisibility of Polynomials over Finite Fields and Combinatorial Applications Designs, Codes and Cryptography anuscript No. (will be inserted by the editor) Divisibility of Polynoials over Finite Fields and Cobinatorial Applications Daniel Panario Olga Sosnovski Brett Stevens Qiang

More information

Chapter 10: Sinusoidal Steady-State Analysis

Chapter 10: Sinusoidal Steady-State Analysis Chapter 0: Sinusoidal Steady-State Analysis Sinusoidal Sources If a circuit is driven by a sinusoidal source, after 5 tie constants, the circuit reaches a steady-state (reeber the RC lab with t = τ). Consequently,

More information

Functions: Review of Algebra and Trigonometry

Functions: Review of Algebra and Trigonometry Sec. and. Functions: Review o Algebra and Trigonoetry A. Functions and Relations DEFN Relation: A set o ordered pairs. (,y) (doain, range) DEFN Function: A correspondence ro one set (the doain) to anther

More information

A proposal for a First-Citation-Speed-Index Link Peer-reviewed author version

A proposal for a First-Citation-Speed-Index Link Peer-reviewed author version A proposal for a First-Citation-Speed-Index Link Peer-reviewed author version Made available by Hasselt University Library in Docuent Server@UHasselt Reference (Published version): EGGHE, Leo; Bornann,

More information

Bernoulli Numbers. Junior Number Theory Seminar University of Texas at Austin September 6th, 2005 Matilde N. Lalín. m 1 ( ) m + 1 k. B m.

Bernoulli Numbers. Junior Number Theory Seminar University of Texas at Austin September 6th, 2005 Matilde N. Lalín. m 1 ( ) m + 1 k. B m. Bernoulli Nubers Junior Nuber Theory Seinar University of Texas at Austin Septeber 6th, 5 Matilde N. Lalín I will ostly follow []. Definition and soe identities Definition 1 Bernoulli nubers are defined

More information

Midterm 1 Sample Solution

Midterm 1 Sample Solution Midter 1 Saple Solution NOTE: Throughout the exa a siple graph is an undirected, unweighted graph with no ultiple edges (i.e., no exact repeats of the sae edge) and no self-loops (i.e., no edges fro a

More information

A general forulation of the cross-nested logit odel Michel Bierlaire, Dpt of Matheatics, EPFL, Lausanne Phone: Fax:

A general forulation of the cross-nested logit odel Michel Bierlaire, Dpt of Matheatics, EPFL, Lausanne Phone: Fax: A general forulation of the cross-nested logit odel Michel Bierlaire, EPFL Conference paper STRC 2001 Session: Choices A general forulation of the cross-nested logit odel Michel Bierlaire, Dpt of Matheatics,

More information

About the definition of parameters and regimes of active two-port networks with variable loads on the basis of projective geometry

About the definition of parameters and regimes of active two-port networks with variable loads on the basis of projective geometry About the definition of paraeters and regies of active two-port networks with variable loads on the basis of projective geoetry PENN ALEXANDR nstitute of Electronic Engineering and Nanotechnologies "D

More information

IN modern society that various systems have become more

IN modern society that various systems have become more Developent of Reliability Function in -Coponent Standby Redundant Syste with Priority Based on Maxiu Entropy Principle Ryosuke Hirata, Ikuo Arizono, Ryosuke Toohiro, Satoshi Oigawa, and Yasuhiko Takeoto

More information

TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES

TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES S. E. Ahed, R. J. Tokins and A. I. Volodin Departent of Matheatics and Statistics University of Regina Regina,

More information

4 = (0.02) 3 13, = 0.25 because = 25. Simi-

4 = (0.02) 3 13, = 0.25 because = 25. Simi- Theore. Let b and be integers greater than. If = (. a a 2 a i ) b,then for any t N, in base (b + t), the fraction has the digital representation = (. a a 2 a i ) b+t, where a i = a i + tk i with k i =

More information

Principles of Optimal Control Spring 2008

Principles of Optimal Control Spring 2008 MIT OpenCourseWare http://ocw.it.edu 16.323 Principles of Optial Control Spring 2008 For inforation about citing these aterials or our Ters of Use, visit: http://ocw.it.edu/ters. 16.323 Lecture 10 Singular

More information

ma x = -bv x + F rod.

ma x = -bv x + F rod. Notes on Dynaical Systes Dynaics is the study of change. The priary ingredients of a dynaical syste are its state and its rule of change (also soeties called the dynaic). Dynaical systes can be continuous

More information

ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS. A Thesis. Presented to. The Faculty of the Department of Mathematics

ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS. A Thesis. Presented to. The Faculty of the Department of Mathematics ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS A Thesis Presented to The Faculty of the Departent of Matheatics San Jose State University In Partial Fulfillent of the Requireents

More information

SOLVING LITERAL EQUATIONS. Bundle 1: Safety & Process Skills

SOLVING LITERAL EQUATIONS. Bundle 1: Safety & Process Skills SOLVING LITERAL EQUATIONS Bundle 1: Safety & Process Skills Solving Literal Equations An equation is a atheatical sentence with an equal sign. The solution of an equation is a value for a variable that

More information

Mechanics Physics 151

Mechanics Physics 151 Mechanics Physics 5 Lecture Oscillations (Chapter 6) What We Did Last Tie Analyzed the otion of a heavy top Reduced into -diensional proble of θ Qualitative behavior Precession + nutation Initial condition

More information

The Simplex Method is Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate

The Simplex Method is Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate The Siplex Method is Strongly Polynoial for the Markov Decision Proble with a Fixed Discount Rate Yinyu Ye April 20, 2010 Abstract In this note we prove that the classic siplex ethod with the ost-negativereduced-cost

More information

12 Towards hydrodynamic equations J Nonlinear Dynamics II: Continuum Systems Lecture 12 Spring 2015

12 Towards hydrodynamic equations J Nonlinear Dynamics II: Continuum Systems Lecture 12 Spring 2015 18.354J Nonlinear Dynaics II: Continuu Systes Lecture 12 Spring 2015 12 Towards hydrodynaic equations The previous classes focussed on the continuu description of static (tie-independent) elastic systes.

More information

Lecture 21 Principle of Inclusion and Exclusion

Lecture 21 Principle of Inclusion and Exclusion Lecture 21 Principle of Inclusion and Exclusion Holden Lee and Yoni Miller 5/6/11 1 Introduction and first exaples We start off with an exaple Exaple 11: At Sunnydale High School there are 28 students

More information

Constant-Space String-Matching. in Sublinear Average Time. (Extended Abstract) Wojciech Rytter z. Warsaw University. and. University of Liverpool

Constant-Space String-Matching. in Sublinear Average Time. (Extended Abstract) Wojciech Rytter z. Warsaw University. and. University of Liverpool Constant-Space String-Matching in Sublinear Average Tie (Extended Abstract) Maxie Crocheore Universite de Marne-la-Vallee Leszek Gasieniec y Max-Planck Institut fur Inforatik Wojciech Rytter z Warsaw University

More information

NON-COMMUTATIVE GRÖBNER BASES FOR COMMUTATIVE ALGEBRAS

NON-COMMUTATIVE GRÖBNER BASES FOR COMMUTATIVE ALGEBRAS PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volue 126, Nuber 3, March 1998, Pages 687 691 S 0002-9939(98)04229-4 NON-COMMUTATIVE GRÖBNER BASES FOR COMMUTATIVE ALGEBRAS DAVID EISENBUD, IRENA PEEVA,

More information

I. Understand get a conceptual grasp of the problem

I. Understand get a conceptual grasp of the problem MASSACHUSETTS INSTITUTE OF TECHNOLOGY Departent o Physics Physics 81T Fall Ter 4 Class Proble 1: Solution Proble 1 A car is driving at a constant but unknown velocity,, on a straightaway A otorcycle is

More information