CHAPTER 2 FUZZY NUMBER AND FUZZY ARITHMETIC

Size: px
Start display at page:

Download "CHAPTER 2 FUZZY NUMBER AND FUZZY ARITHMETIC"

Transcription

1 CHPTER FUZZY NUMBER ND FUZZY RITHMETIC 1 Introdction Fzzy rithmetic or rithmetic of fzzy nmbers is generlistion of intervl rithmetic, where rther thn considering intervls t one constnt level only, severl levels re considered in [0, 1] This is becse, the definition of fzzy set which llows degree of membership for n element of the niversl set It plys n importnt role in mny pplictions, sy, fzzy control, decision mking, pproximte resoning, optimiztion nd sttistics with imprecise probbilities Some pproprite reference for this chpter re Dbois nd Prde [14] nd [15], Kfmnn nd Gpt [1] nd [] nd Moore [39] Fzzy rithmetic 1 Intervl rithmetic The fndmentls of fzzy rithmetic is nothing bt intervl rithmetic In given closed intervl R, how to dd, sbtrct, mltiply nd divide These intervl in R is lso clled n intervl of confidence s its limits the ncertinty of dt to n intervl definitions Let = [1, ] nd B= [b1, b] be two closed intervl in R then we hve following Definition: (ddition nd Sbtrction) x 1 1 If [, ], y [b, b ], then x y [1 b1, b] nd x y [1 b1, b] 3

2 therefore +B = [1, ] + [b1, b] = [1+b1, +b] B = [1, ] - [b1, b] = [1-b, -b1] Exmple: 3 [, 5] + [1, 3] = [3, 8] [0, 1] [ 6, 5] = [ 5, 7] Definition 4 (Imge of n intervl) x 1 then its imge x, If [, ] by is defined s 1 Therefore the imge of is denoted,, 1 1 Definition: 5 (Mltipliction) The mltipliction of two closed intervls = [1, ] nd B = [b1, b] of R denoted by B is defined s B = [min (1b1, 1b, b1, b), mx (1b1, 1b, b1, b)] Exmple: 6, 05,, 05, mx, 05,, 05 [ 1, 1] [, 05] min [,] 4

3 Definition: 7 (Sclr Mltipliction nd Inverse) Let, be closed intervl in R nd kr identifying the sclr k s the 1 closed intervl [k, k], the sclr mltipliction k is defined s k = [k, k] [1, ] = [k1, k] for [1, ] R if x [1, ] nd if 0[ 1, ] then x 1 Therefore the inverse of is denoted by 1 nd it is defined s [1, ], provided 0 [1, ] 1 Definition: 8 (Division) The division of two closed intervls = [1, ] nd B = [b1, b] of R denoted by /B is defined s the mltipliction [1, ] nd 1 b 1 b 1 provided 0[b1, b] Therefore /B = [1, ] / [b1, b] 1 1 = [1, ], b b 1 = min,,,,mx,,, b b1 b b1 b b1 b b1 Exmple: 9 [4, 10] / [1, ] = [, 10] 5

4 rithmetic opertions on closed intervls stisfy some sefl properties, to overview, let = [1, ], B = [b1, b], C = [c1, c], 0 = [0, 0] nd 1= [1, 1], sing these symbols, the properties re formlted s follows: 1 +B = B+ nd B = B (Commttive) (+B)+C = + (B+C) nd (BC) = ( B) C (ssocitive) 3 =0+ = +0 nd =1 = 1 (Identity) 4 (B+C) B+ C (Sbdistribtivity) 5 If b c) 0, forevery b B, c C, then (B C) B C(Distribtive Frthermore, if = [, ] then (B+C) = B + C 6 0 in nd 1 in / 7 If E nd B F then B E F, B E F, B E F, / B E/ F (Inclsion monotonicity) s n exmple we prove only the less obvios properties of Sbdistribtivity First we hve (B+C) = {(b+c) /, b B, c C} = { b+ c /, bb, cc } { b ' c/ ', b B, c C }= B + C Hence (B+C) B+ C b1 1 ssme now withot loss of generlity, tht 0, c 0 Then we hve to consider the following three cses: 1 If 1 0then (B+C) = [1 (b1+c1), (b+c)] = [1 b1+ b] + [1 c1, c] 6

5 = B + C If 1 < 0 nd 0 then 0, ()=[, 1] nd () (B+C) = ( ) B + ( ) C Hence (B+C) = B+ C 3 If 1 < 0 nd > 0 then (B+C) = [1 (b+c), (b+c)] = [1 b, b] + [1 c, c] = B + C To show tht distribtivity does not hold in generl, Let = [0, 1], B = [1, ], C = [, 1], then B = [0, ], C = [, 0], B+C = [ 1, 1] nd (B+C) = [ 1, 1] [, ] = B + C Definition 10 (Mx nd min opertions) Let = [1, ] nd B = [b1, b] be two closed intervls in R then the Mx nd min opertions on nd B re defined s B [1, ] [b1, b ] [1 b1, b ] B [1, ] [b1, b ] [1 b1, b ] Note: 11 It cn be verified tht ddition nd mltipliction opertions on closed intervls s defined bove re commttive nd ssocitive bt sbtrction nd division re neither commttive nor ssocitive + ' = [1, ] + [, 1] [0, 0] = 0 7

6 In cse = [1, ] R nd 0 [1, ], then -1 = -1 [1, 1] 1 Note: 1 In the next section, fzzy nmbers nd fzzy rithmetic re introdced It is more significnt in rithmetic of cts which re closed nd bonded intervls of type,, (0,1], when fzzy set in R is fzzy nmber Therefore ll ides presented in this section cn be borrowed for intervls of type,, (0,1] rithmetic of fzzy nmbers cn be developed nd meningfl 3 Fzzy nmber nd their representtion There re mny in rel life sittion, in which, the res like decision mking nd optimiztion, where rther thn deling with crisp rel nmbers nd crisp intervls one hs to del with pproximtion of nmbers which re close to given rel nmber The prpose of this section is to nderstnd, how fzzy sttement cn be conceptlized by certin pproprite fzzy sets in R to be termed s fzzy nmbers Let s consider fzzy sttement the nmbers tht re closed to given nmber r since r in R is close to itself, ny fzzy set in R which represents the fzzy sttement shold hve property tht (r) 1 Which imply mst be norml fzzy set lso, jst prescribing n intervl rond r is not enogh The intervl shold be considered t vrying levels (0,1] to hve proper grdtion of cts in nd it mst be closed intervl of type, for(0,1] Frther ] tht spport of is bonded (0, 1 mst be of finite length nd for tht one needs 8

7 Definition 31 (Fzzy nmber) fzzy set in R is clled fzzy nmber if it stisfies the following conditions: 1 is norml fzzy set is closed intervl for every (0,1] 3 Spport of is bonded Theorem 3 Let be fzzy set in R then is fzzy nmber if nd only if there exists closed intervl (which my be singleton) [, b] sch tht 1 if x [,b] (x) (x) if x (,) r(x) if x (b, ) Where i) : (-, ) [0, 1] is monotonic incresing, continos from the right sch tht (x) = 0 for x in ii) r :(b, ) 0, 1, k, k1 < is monotonic decresing, continos form the left sch tht r(x) = 0 for x in (k, ), k > b Note: 33 In cse the membership fnction of the fzzy set in R tkes the form 1 (x) 0 if x if x 9

8 It becomes the chrcteristic fnction of the singleton set {} nd therefore it represents the rel nmber The following figre exhibits both continos fnction (x) nd r(x) re hving continity in the membership Note: 34 Fzzy set in X is convex set if nd only if ll its α-cts α re convex crisp sets for [0,1] Frther when the membership fnction of the convex fzzy set in R is pper semi-continos, then ll these α-cts α for (0,1] re closed intervls Since the bsic reqirement to define fzzy nmber is tht ll it (0,1] re closed nd bonded intervls The following is n lternte definition of fzzy nmber Definition: 35 fzzy sbset of the rel line R with membership fnction : R [0, 1] is clled fzzy nmber if 1 is norml there exists n element x0 sch tht (x0) = 1 is convex, (x1 + (1-)x) (x1) Λ (x) (x1, x) R nd [0, 1] 30

9 3 is pper semi-continos 4 Spport of is bonded, where Spp = {x R: (x) 0} 4 rithmetic of fzzy nmbers rithmetic of fzzy nmbers re defined by the following methods: 1 Intervl rithmetic on α-cts of given fzzy nmbers Mthemticl pproch which decomposes fzzy set in terms of specil fzzy set, (0, 1] 3 Zdeh s extension principle 41 pproch on α-cts Let nd B be ny two fzzy nmbers nd [, ] nd B [b, b ] be cts where (0, 1] of nd B respectively Let * denote ny rithmetic opertions, on fzzy nmbers, then we hve following definitions: Definition 4 (Opertions on two fzzy nmbers) Let nd B be ny two fzzy sets Let nd B be fzzy nmbers, then * opertion on fzzy nmbers gives fzzy nmbers in R B ( B) nd B B, (0, 1] Here B be fzzy nmber bt not generl fzzy set The sets B,, B, re ll closed intervls for (0, 1] lso for given in (0, 1], the closed intervl ( B) cn be compted by pplying the intervl rithmetic on the closed intervls respect to the opertions * nd B with 31

10 L R In prticlr, B [ b, b ] L R B [ b, b ] Frther, fzzy nmber in R, k > 0 cn gin be defined s erlier in the context of intervl rithmetic k k [k,k ] 5 pproch sing Zdeh s extension principle Let nd B two fzzy nmbers nd * be ny of the rithmetic opertions described bove Using extension principle, fzzy nmber *B is defined s sp min μ B (z) = zxy μ (x), μ B (y) z in R In prticlr we hve Z) sp minμ (x), μ (y) B( B zxy B B ( z) sp min μ (x), μ B(y) zxy ( z) sp min μ (x), μ B (y) zxy Z) spmin μ (x), μ (y) ( B x B z y 51 Specil types of fzzy nmbers nd their rithmetic Some specil types of fzzy nmbers nd fzzy rithmetic re discssed here, which will be sed extensively in lter Chpters on fzzy mthemticl progrmming nd fzzy gmes 3

11 Definition 5 (Tringlr fzzy nmber (TFN)) fzzy nmber is clled tringlr fzzy nmber (TFN) if its membership fnction is defined by μ 0 x (x) x x, x x x The TFN is denoted by triplet (3-tples) =,, nd hs the shpe of tringle shown below is the closed intervl Frther the cts of the TFN,, [, ] = ( )α, ( )α (0, 1] Next =,, nd B=b, b, two TFN then sing one cn compte *B where opertion * my be +, -, *, /,, b In this context B b, b, b,,,, 33

12 k= k, k, k, k > 0, B = b, b, b re TFN bt B, 1, / B, B, B need not be TFN Exmple: 53 [1, ] Let = (-3,, 4), B= (-1, 0, 5) be two TFN s then sing the formle for the ddition nd sbtrction of TFN s +B = (-3,, 4) + (-1, 0, 5) = (-4,, 9) -B = (-3,, 4) - (-1, 0, 5) = (-8,, 5) Using the cts α nd B α for the given fzzy nmber nd B we hve [, ] = ( ) α, ( ) α (0,1], = ( 3) 3, () 4, (0,1] 5α 3, α 4, (0,1 = ] nd B [b,b ] = ] (b b )α b, (b b) α b (0,1 = α 1, 5α 5, (0,1] B 5 3, 4 1, 5 5, (0,1 Therefore ] = 6 4, 7 9 [c,c ] (sy), (0,1] To find the membership fnction of B(x), we hve to find the rnge x in R where α level sets re vlid Ths c L, 34

13 6 4 x 7 9 if if x 4, from c 6 9 x, from c 7 L R frther α becomes, for x = the membership fnction becomes 0 x 4 B (x) 6 9 x 7 if if if x 4 4 x x 9 or x 9 Which is tringlr fzzy nmber (TFN) (-4,, 9) s shown in the below given digrm The following exmple shows B need not be TFN in generl: Exmple: 54 [1, ] Let = (, 3, 5) nd B = (1, 4, 8) be two TFN in R s noted erlier one hs to compte B by the first principle sing α-cts nd B where, 5 nd B 3 1,

14 B 3 1, , c, c For,, B,40nd for, B 1, Therefore membership fnction B tkes 1 for x = 1 nd 0 for x < nd lso for x > 40 lso in between nd 1 nd lso between 1 nd 40, the segments of the membership fnctions re not stright lines bt it is prbol For this it is fond tht the rnge x in R, in which α level set re vlid This cn be ccomplished from L c by solving x x x 6 Here only + sign will be tken becse t x=1, α = 1 nd α cnnot be negtive Similrly one hs to solve x x 5 Therefore membership fnction B x x 5 if x or x 40 if x 1 if 1 x 40 Which is not the membership of TFN nd it cn be seen from the digrm 36

15 For more detils in tringlr pproximtions of fzzy one cn refer Kffmnn nd Gpt [0, 1] nd Dbois nd Prde [14, 15] Definition 55 (Trpezoidl fzzy nmber TrFN) fzzy nmber is clled trpezoidl fzzy nmber (TrFN) if its membership fnction μ is given by μ 0 x (x) 1 x if if if x x x, x if x The TrFN is denoted by qdrplet (4-tples) =,,, nd hs the shpe of trpezoid 37

16 The TrFN is denoted by qdrplet =,,, nd hs the shpe of trpezoid Frther α-ct of TrFN =,,, is the closed intervl α =[ α L, α R ] = )α, ( )α where [0,1] ( Next =,,, nd B= b,b,b, two TFN s then sing one cn compte *B b where opertion * my be +, -, *, /,, In this context it cn be verified B b, b, b, b, B b, b, b, b nd k = k, k, k, k k > 0 re TrFN bt -1, B, / B, B nd B need not be TrFN 38

17 Definition 56 (Left Right fzzy nmber) fzzy nmber is clled n L-R fzzy nmber if its membership fnction μ : X [0, 1] hs the following form: x L α 1 μ (x) x b R β 0 if α x, α 0 if x b if b x b β, β 0 otherwise The L-R fzzy nmber s described bove nd it is denoted by (,b,, ) LR Here L nd R re clled strting s the left nd right reference fnctions, nd b re respectively clled strting nd end points of flt intervl, is clled the left spred nd is clled the right spred The generl shpe of n L-R fzzy nmber will s follows: Let ( 1,b,α,β) nd B(,b,γ, δ) 1 LR LR be two L-R fzzy nmbers then it cn be verified tht 39

18 B (, b b, α γ, β δ) 1 1 LR B ( b, b, α δ,β γ) 1 1 LR Frther, similr to TFN nd TrFN, -1, B, / B re not L-R fzzy nmbers in generl nd it needs certin L-R pproximtions if they re to be sed s pproximte L-R fzzy nmbers 6 Rnking of fzzy nmbers Rnking of fzzy nmber plys importnt role in fzzy mthemticl progrmming nd fzzy gmes Let N(R) be the set of ll fzzy nmbers in R nd, B in N(R) Let F: N(R) R, clled rnking fnction or rnking index is defined nd F () F (B) is treted s eqivlent to B Since F () = F (B), in generl, it does not men =B This rnking is to be nderstood in the sense of eqivlence clsses only Yger [59] proposed the following indices h () 1 xμ μ (x)dx (x)dx where nd re the lower nd pper limits of the spport of The vle h1 () represents the centroid of the fzzy nmber in N(R) If in prticlr =,, is TFN, then nd re the lower nd pper limits of the spport of Here is the modl vle verified tht In this cse by ctl sbstittion of the membership fnction of the TFN, it cn be 40

19 h1() 3 Therefore for given two TFN s =,,, B =, b, b b B with respect to h1 if nd only if,, b, b, b mx h () = m, d, where α mx is the height of 1, α = 0 α ct, where α in (0, 1] nd m ct For TFN =,, α mx =1 nd α =, L R m, L R, L R is n is the men vle of elements of tht n α- = ), ( ) ( α, α = ( ) h () 4 In this view of the bove, we conclde tht given two TFN =,, nd B = b b, b, B with respect to h if nd only if,, b b b Chpter 5 The pplictions of the bove fzzy nmbers shll be discssed in Chpter 3 nd 41

20 MATHEMATICS POLYNOMIALS

20 MATHEMATICS POLYNOMIALS 0 MATHEMATICS POLYNOMIALS.1 Introduction In Clss IX, you hve studied polynomils in one vrible nd their degrees. Recll tht if p(x) is polynomil in x, the highest power of x in p(x) is clled the degree of

More information

The Regulated and Riemann Integrals

The Regulated and Riemann Integrals Chpter 1 The Regulted nd Riemnn Integrls 1.1 Introduction We will consider severl different pproches to defining the definite integrl f(x) dx of function f(x). These definitions will ll ssign the sme vlue

More information

Review of Calculus, cont d

Review of Calculus, cont d Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some

More information

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite Unit #8 : The Integrl Gols: Determine how to clculte the re described by function. Define the definite integrl. Eplore the reltionship between the definite integrl nd re. Eplore wys to estimte the definite

More information

Intuitionistic Fuzzy Lattices and Intuitionistic Fuzzy Boolean Algebras

Intuitionistic Fuzzy Lattices and Intuitionistic Fuzzy Boolean Algebras Intuitionistic Fuzzy Lttices nd Intuitionistic Fuzzy oolen Algebrs.K. Tripthy #1, M.K. Stpthy *2 nd P.K.Choudhury ##3 # School of Computing Science nd Engineering VIT University Vellore-632014, TN, Indi

More information

Overview of Calculus I

Overview of Calculus I Overview of Clculus I Prof. Jim Swift Northern Arizon University There re three key concepts in clculus: The limit, the derivtive, nd the integrl. You need to understnd the definitions of these three things,

More information

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac REVIEW OF ALGEBRA Here we review the bsic rules nd procedures of lgebr tht you need to know in order to be successful in clculus. ARITHMETIC OPERATIONS The rel numbers hve the following properties: b b

More information

Definite integral. Mathematics FRDIS MENDELU

Definite integral. Mathematics FRDIS MENDELU Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová Brno 1 Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function defined on [, b]. Wht is the re of the

More information

Math 1B, lecture 4: Error bounds for numerical methods

Math 1B, lecture 4: Error bounds for numerical methods Mth B, lecture 4: Error bounds for numericl methods Nthn Pflueger 4 September 0 Introduction The five numericl methods descried in the previous lecture ll operte by the sme principle: they pproximte the

More information

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams Chpter 4 Contrvrince, Covrince, nd Spcetime Digrms 4. The Components of Vector in Skewed Coordintes We hve seen in Chpter 3; figure 3.9, tht in order to show inertil motion tht is consistent with the Lorentz

More information

Definite integral. Mathematics FRDIS MENDELU. Simona Fišnarová (Mendel University) Definite integral MENDELU 1 / 30

Definite integral. Mathematics FRDIS MENDELU. Simona Fišnarová (Mendel University) Definite integral MENDELU 1 / 30 Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová (Mendel University) Definite integrl MENDELU / Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function

More information

Continuous Random Variables

Continuous Random Variables STAT/MATH 395 A - PROBABILITY II UW Winter Qurter 217 Néhémy Lim Continuous Rndom Vribles Nottion. The indictor function of set S is rel-vlued function defined by : { 1 if x S 1 S (x) if x S Suppose tht

More information

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics SCHOOL OF ENGINEERING & BUIL ENVIRONMEN Mthemtics An Introduction to Mtrices Definition of Mtri Size of Mtri Rows nd Columns of Mtri Mtri Addition Sclr Multipliction of Mtri Mtri Multipliction 7 rnspose

More information

R. I. Badran Solid State Physics

R. I. Badran Solid State Physics I Bdrn Solid Stte Physics Crystl vibrtions nd the clssicl theory: The ssmption will be mde to consider tht the men eqilibrim position of ech ion is t Brvis lttice site The ions oscillte bot this men position

More information

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by. NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with

More information

Chapter 0. What is the Lebesgue integral about?

Chapter 0. What is the Lebesgue integral about? Chpter 0. Wht is the Lebesgue integrl bout? The pln is to hve tutoril sheet ech week, most often on Fridy, (to be done during the clss) where you will try to get used to the ides introduced in the previous

More information

Math 8 Winter 2015 Applications of Integration

Math 8 Winter 2015 Applications of Integration Mth 8 Winter 205 Applictions of Integrtion Here re few importnt pplictions of integrtion. The pplictions you my see on n exm in this course include only the Net Chnge Theorem (which is relly just the Fundmentl

More information

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1 MATH34032: Green s Functions, Integrl Equtions nd the Clculus of Vritions 1 Section 1 Function spces nd opertors Here we gives some brief detils nd definitions, prticulrly relting to opertors. For further

More information

Lecture 20: Numerical Integration III

Lecture 20: Numerical Integration III cs4: introduction to numericl nlysis /8/0 Lecture 0: Numericl Integrtion III Instructor: Professor Amos Ron Scribes: Mrk Cowlishw, Yunpeng Li, Nthnel Fillmore For the lst few lectures we hve discussed

More information

AQA Further Pure 1. Complex Numbers. Section 1: Introduction to Complex Numbers. The number system

AQA Further Pure 1. Complex Numbers. Section 1: Introduction to Complex Numbers. The number system Complex Numbers Section 1: Introduction to Complex Numbers Notes nd Exmples These notes contin subsections on The number system Adding nd subtrcting complex numbers Multiplying complex numbers Complex

More information

Before we can begin Ch. 3 on Radicals, we need to be familiar with perfect squares, cubes, etc. Try and do as many as you can without a calculator!!!

Before we can begin Ch. 3 on Radicals, we need to be familiar with perfect squares, cubes, etc. Try and do as many as you can without a calculator!!! Nme: Algebr II Honors Pre-Chpter Homework Before we cn begin Ch on Rdicls, we need to be fmilir with perfect squres, cubes, etc Try nd do s mny s you cn without clcultor!!! n The nth root of n n Be ble

More information

3.4 Numerical integration

3.4 Numerical integration 3.4. Numericl integrtion 63 3.4 Numericl integrtion In mny economic pplictions it is necessry to compute the definite integrl of relvlued function f with respect to "weight" function w over n intervl [,

More information

Realistic Method for Solving Fully Intuitionistic Fuzzy. Transportation Problems

Realistic Method for Solving Fully Intuitionistic Fuzzy. Transportation Problems Applied Mthemticl Sciences, Vol 8, 201, no 11, 6-69 HKAR Ltd, wwwm-hikricom http://dxdoiorg/10988/ms20176 Relistic Method for Solving Fully ntuitionistic Fuzzy Trnsporttion Problems P Pndin Deprtment of

More information

Euler, Ioachimescu and the trapezium rule. G.J.O. Jameson (Math. Gazette 96 (2012), )

Euler, Ioachimescu and the trapezium rule. G.J.O. Jameson (Math. Gazette 96 (2012), ) Euler, Iochimescu nd the trpezium rule G.J.O. Jmeson (Mth. Gzette 96 (0), 36 4) The following results were estblished in recent Gzette rticle [, Theorems, 3, 4]. Given > 0 nd 0 < s

More information

p-adic Egyptian Fractions

p-adic Egyptian Fractions p-adic Egyptin Frctions Contents 1 Introduction 1 2 Trditionl Egyptin Frctions nd Greedy Algorithm 2 3 Set-up 3 4 p-greedy Algorithm 5 5 p-egyptin Trditionl 10 6 Conclusion 1 Introduction An Egyptin frction

More information

Lecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar)

Lecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar) Lecture 3 (5.3.2018) (trnslted nd slightly dpted from lecture notes by Mrtin Klzr) Riemnn integrl Now we define precisely the concept of the re, in prticulr, the re of figure U(, b, f) under the grph of

More information

Lecture 1. Functional series. Pointwise and uniform convergence.

Lecture 1. Functional series. Pointwise and uniform convergence. 1 Introduction. Lecture 1. Functionl series. Pointwise nd uniform convergence. In this course we study mongst other things Fourier series. The Fourier series for periodic function f(x) with period 2π is

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn

More information

The final exam will take place on Friday May 11th from 8am 11am in Evans room 60.

The final exam will take place on Friday May 11th from 8am 11am in Evans room 60. Mth 104: finl informtion The finl exm will tke plce on Fridy My 11th from 8m 11m in Evns room 60. The exm will cover ll prts of the course with equl weighting. It will cover Chpters 1 5, 7 15, 17 21, 23

More information

y b y y sx 2 y 2 z CHANGE OF VARIABLES IN MULTIPLE INTEGRALS

y b y y sx 2 y 2 z CHANGE OF VARIABLES IN MULTIPLE INTEGRALS ECION.8 CHANGE OF VAIABLE IN MULIPLE INEGAL 73 CA tive -is psses throgh the point where the prime meridin (the meridin throgh Greenwich, Englnd) intersects the eqtor. hen the ltitde of P is nd the longitde

More information

Sections 5.2: The Definite Integral

Sections 5.2: The Definite Integral Sections 5.2: The Definite Integrl In this section we shll formlize the ides from the lst section to functions in generl. We strt with forml definition.. The Definite Integrl Definition.. Suppose f(x)

More information

III. Lecture on Numerical Integration. File faclib/dattab/lecture-notes/numerical-inter03.tex /by EC, 3/14/2008 at 15:11, version 9

III. Lecture on Numerical Integration. File faclib/dattab/lecture-notes/numerical-inter03.tex /by EC, 3/14/2008 at 15:11, version 9 III Lecture on Numericl Integrtion File fclib/dttb/lecture-notes/numerical-inter03.tex /by EC, 3/14/008 t 15:11, version 9 1 Sttement of the Numericl Integrtion Problem In this lecture we consider the

More information

8 Laplace s Method and Local Limit Theorems

8 Laplace s Method and Local Limit Theorems 8 Lplce s Method nd Locl Limit Theorems 8. Fourier Anlysis in Higher DImensions Most of the theorems of Fourier nlysis tht we hve proved hve nturl generliztions to higher dimensions, nd these cn be proved

More information

10 Vector Integral Calculus

10 Vector Integral Calculus Vector Integrl lculus Vector integrl clculus extends integrls s known from clculus to integrls over curves ("line integrls"), surfces ("surfce integrls") nd solids ("volume integrls"). These integrls hve

More information

Chapter 14. Matrix Representations of Linear Transformations

Chapter 14. Matrix Representations of Linear Transformations Chpter 4 Mtrix Representtions of Liner Trnsformtions When considering the Het Stte Evolution, we found tht we could describe this process using multipliction by mtrix. This ws nice becuse computers cn

More information

Chapter 5 : Continuous Random Variables

Chapter 5 : Continuous Random Variables STAT/MATH 395 A - PROBABILITY II UW Winter Qurter 216 Néhémy Lim Chpter 5 : Continuous Rndom Vribles Nottions. N {, 1, 2,...}, set of nturl numbers (i.e. ll nonnegtive integers); N {1, 2,...}, set of ll

More information

Taylor Polynomial Inequalities

Taylor Polynomial Inequalities Tylor Polynomil Inequlities Ben Glin September 17, 24 Abstrct There re instnces where we my wish to pproximte the vlue of complicted function round given point by constructing simpler function such s polynomil

More information

Pre-Session Review. Part 1: Basic Algebra; Linear Functions and Graphs

Pre-Session Review. Part 1: Basic Algebra; Linear Functions and Graphs Pre-Session Review Prt 1: Bsic Algebr; Liner Functions nd Grphs A. Generl Review nd Introduction to Algebr Hierrchy of Arithmetic Opertions Opertions in ny expression re performed in the following order:

More information

Partial Derivatives. Limits. For a single variable function f (x), the limit lim

Partial Derivatives. Limits. For a single variable function f (x), the limit lim Limits Prtil Derivtives For single vrible function f (x), the limit lim x f (x) exists only if the right-hnd side limit equls to the left-hnd side limit, i.e., lim f (x) = lim f (x). x x + For two vribles

More information

New Expansion and Infinite Series

New Expansion and Infinite Series Interntionl Mthemticl Forum, Vol. 9, 204, no. 22, 06-073 HIKARI Ltd, www.m-hikri.com http://dx.doi.org/0.2988/imf.204.4502 New Expnsion nd Infinite Series Diyun Zhng College of Computer Nnjing University

More information

f(x)dx . Show that there 1, 0 < x 1 does not exist a differentiable function g : [ 1, 1] R such that g (x) = f(x) for all

f(x)dx . Show that there 1, 0 < x 1 does not exist a differentiable function g : [ 1, 1] R such that g (x) = f(x) for all 3 Definite Integrl 3.1 Introduction In school one comes cross the definition of the integrl of rel vlued function defined on closed nd bounded intervl [, b] between the limits nd b, i.e., f(x)dx s the

More information

We are looking for ways to compute the integral of a function f(x), f(x)dx.

We are looking for ways to compute the integral of a function f(x), f(x)dx. INTEGRATION TECHNIQUES Introdction We re looking for wys to compte the integrl of fnction f(x), f(x)dx. To pt it simply, wht we need to do is find fnction F (x) sch tht F (x) = f(x). Then if the integrl

More information

NEW INEQUALITIES OF SIMPSON S TYPE FOR s CONVEX FUNCTIONS WITH APPLICATIONS. := f (4) (x) <. The following inequality. 2 b a

NEW INEQUALITIES OF SIMPSON S TYPE FOR s CONVEX FUNCTIONS WITH APPLICATIONS. := f (4) (x) <. The following inequality. 2 b a NEW INEQUALITIES OF SIMPSON S TYPE FOR s CONVEX FUNCTIONS WITH APPLICATIONS MOHAMMAD ALOMARI A MASLINA DARUS A AND SEVER S DRAGOMIR B Abstrct In terms of the first derivtive some ineulities of Simpson

More information

Theoretical foundations of Gaussian quadrature

Theoretical foundations of Gaussian quadrature Theoreticl foundtions of Gussin qudrture 1 Inner product vector spce Definition 1. A vector spce (or liner spce) is set V = {u, v, w,...} in which the following two opertions re defined: (A) Addition of

More information

Numerical Integration

Numerical Integration Chpter 5 Numericl Integrtion Numericl integrtion is the study of how the numericl vlue of n integrl cn be found. Methods of function pproximtion discussed in Chpter??, i.e., function pproximtion vi the

More information

4.4 Areas, Integrals and Antiderivatives

4.4 Areas, Integrals and Antiderivatives . res, integrls nd ntiderivtives 333. Ares, Integrls nd Antiderivtives This section explores properties of functions defined s res nd exmines some connections mong res, integrls nd ntiderivtives. In order

More information

APPROXIMATE INTEGRATION

APPROXIMATE INTEGRATION APPROXIMATE INTEGRATION. Introduction We hve seen tht there re functions whose nti-derivtives cnnot be expressed in closed form. For these resons ny definite integrl involving these integrnds cnnot be

More information

CS 275 Automata and Formal Language Theory

CS 275 Automata and Formal Language Theory CS 275 Automt nd Forml Lnguge Theory Course Notes Prt II: The Recognition Problem (II) Chpter II.5.: Properties of Context Free Grmmrs (14) Anton Setzer (Bsed on book drft by J. V. Tucker nd K. Stephenson)

More information

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus Unit #9 : Definite Integrl Properties; Fundmentl Theorem of Clculus Gols: Identify properties of definite integrls Define odd nd even functions, nd reltionship to integrl vlues Introduce the Fundmentl

More information

Solution to Fredholm Fuzzy Integral Equations with Degenerate Kernel

Solution to Fredholm Fuzzy Integral Equations with Degenerate Kernel Int. J. Contemp. Mth. Sciences, Vol. 6, 2011, no. 11, 535-543 Solution to Fredholm Fuzzy Integrl Equtions with Degenerte Kernel M. M. Shmivnd, A. Shhsvrn nd S. M. Tri Fculty of Science, Islmic Azd University

More information

Math 360: A primitive integral and elementary functions

Math 360: A primitive integral and elementary functions Mth 360: A primitive integrl nd elementry functions D. DeTurck University of Pennsylvni October 16, 2017 D. DeTurck Mth 360 001 2017C: Integrl/functions 1 / 32 Setup for the integrl prtitions Definition:

More information

Introduction to Group Theory

Introduction to Group Theory Introduction to Group Theory Let G be n rbitrry set of elements, typiclly denoted s, b, c,, tht is, let G = {, b, c, }. A binry opertion in G is rule tht ssocites with ech ordered pir (,b) of elements

More information

Direction of bifurcation for some non-autonomous problems

Direction of bifurcation for some non-autonomous problems Direction of bifrction for some non-tonomos problems Philip Kormn Deprtment of Mthemticl Sciences University of Cincinnti Cincinnti Ohio 45221-25 Abstrct We stdy the exct mltiplicity of positive soltions,

More information

Physics I Math Assessment with Answers

Physics I Math Assessment with Answers Physics I Mth Assessment with Answers The prpose of the following 10 qestions is to ssess some mth skills tht yo will need in Physics I These qestions will help yo identify some mth res tht yo my wnt to

More information

set is not closed under matrix [ multiplication, ] and does not form a group.

set is not closed under matrix [ multiplication, ] and does not form a group. Prolem 2.3: Which of the following collections of 2 2 mtrices with rel entries form groups under [ mtrix ] multipliction? i) Those of the form for which c d 2 Answer: The set of such mtrices is not closed

More information

The First Fundamental Theorem of Calculus. If f(x) is continuous on [a, b] and F (x) is any antiderivative. f(x) dx = F (b) F (a).

The First Fundamental Theorem of Calculus. If f(x) is continuous on [a, b] and F (x) is any antiderivative. f(x) dx = F (b) F (a). The Fundmentl Theorems of Clculus Mth 4, Section 0, Spring 009 We now know enough bout definite integrls to give precise formultions of the Fundmentl Theorems of Clculus. We will lso look t some bsic emples

More information

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007 A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus

More information

Finite Automata. Informatics 2A: Lecture 3. John Longley. 22 September School of Informatics University of Edinburgh

Finite Automata. Informatics 2A: Lecture 3. John Longley. 22 September School of Informatics University of Edinburgh Lnguges nd Automt Finite Automt Informtics 2A: Lecture 3 John Longley School of Informtics University of Edinburgh jrl@inf.ed.c.uk 22 September 2017 1 / 30 Lnguges nd Automt 1 Lnguges nd Automt Wht is

More information

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1 3 9. SEQUENCES AND SERIES 63. Representtion of functions s power series Consider power series x 2 + x 4 x 6 + x 8 + = ( ) n x 2n It is geometric series with q = x 2 nd therefore it converges for ll q =

More information

Best Approximation in the 2-norm

Best Approximation in the 2-norm Jim Lmbers MAT 77 Fll Semester 1-11 Lecture 1 Notes These notes correspond to Sections 9. nd 9.3 in the text. Best Approximtion in the -norm Suppose tht we wish to obtin function f n (x) tht is liner combintion

More information

Stuff You Need to Know From Calculus

Stuff You Need to Know From Calculus Stuff You Need to Know From Clculus For the first time in the semester, the stuff we re doing is finlly going to look like clculus (with vector slnt, of course). This mens tht in order to succeed, you

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Introduction Lecture 3 Gussin Probbility Distribution Gussin probbility distribution is perhps the most used distribution in ll of science. lso clled bell shped curve or norml distribution Unlike the binomil

More information

Topics Covered AP Calculus AB

Topics Covered AP Calculus AB Topics Covered AP Clculus AB ) Elementry Functions ) Properties of Functions i) A function f is defined s set of ll ordered pirs (, y), such tht for ech element, there corresponds ectly one element y.

More information

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER /2019

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER /2019 ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS MATH00030 SEMESTER 208/209 DR. ANTHONY BROWN 7.. Introduction to Integrtion. 7. Integrl Clculus As ws the cse with the chpter on differentil

More information

UNIFORM CONVERGENCE. Contents 1. Uniform Convergence 1 2. Properties of uniform convergence 3

UNIFORM CONVERGENCE. Contents 1. Uniform Convergence 1 2. Properties of uniform convergence 3 UNIFORM CONVERGENCE Contents 1. Uniform Convergence 1 2. Properties of uniform convergence 3 Suppose f n : Ω R or f n : Ω C is sequence of rel or complex functions, nd f n f s n in some sense. Furthermore,

More information

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions Physics 6C Solution of inhomogeneous ordinry differentil equtions using Green s functions Peter Young November 5, 29 Homogeneous Equtions We hve studied, especilly in long HW problem, second order liner

More information

Here we study square linear systems and properties of their coefficient matrices as they relate to the solution set of the linear system.

Here we study square linear systems and properties of their coefficient matrices as they relate to the solution set of the linear system. Section 24 Nonsingulr Liner Systems Here we study squre liner systems nd properties of their coefficient mtrices s they relte to the solution set of the liner system Let A be n n Then we know from previous

More information

Chapters 4 & 5 Integrals & Applications

Chapters 4 & 5 Integrals & Applications Contents Chpters 4 & 5 Integrls & Applictions Motivtion to Chpters 4 & 5 2 Chpter 4 3 Ares nd Distnces 3. VIDEO - Ares Under Functions............................................ 3.2 VIDEO - Applictions

More information

Mapping the delta function and other Radon measures

Mapping the delta function and other Radon measures Mpping the delt function nd other Rdon mesures Notes for Mth583A, Fll 2008 November 25, 2008 Rdon mesures Consider continuous function f on the rel line with sclr vlues. It is sid to hve bounded support

More information

Review of basic calculus

Review of basic calculus Review of bsic clculus This brief review reclls some of the most importnt concepts, definitions, nd theorems from bsic clculus. It is not intended to tech bsic clculus from scrtch. If ny of the items below

More information

ECO 317 Economics of Uncertainty Fall Term 2007 Notes for lectures 4. Stochastic Dominance

ECO 317 Economics of Uncertainty Fall Term 2007 Notes for lectures 4. Stochastic Dominance Generl structure ECO 37 Economics of Uncertinty Fll Term 007 Notes for lectures 4. Stochstic Dominnce Here we suppose tht the consequences re welth mounts denoted by W, which cn tke on ny vlue between

More information

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b.

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b. Mth 255 - Vector lculus II Notes 4.2 Pth nd Line Integrls We begin with discussion of pth integrls (the book clls them sclr line integrls). We will do this for function of two vribles, but these ides cn

More information

Infinite Geometric Series

Infinite Geometric Series Infinite Geometric Series Finite Geometric Series ( finite SUM) Let 0 < r < 1, nd let n be positive integer. Consider the finite sum It turns out there is simple lgebric expression tht is equivlent to

More information

1 The Lagrange interpolation formula

1 The Lagrange interpolation formula Notes on Qudrture 1 The Lgrnge interpoltion formul We briefly recll the Lgrnge interpoltion formul. The strting point is collection of N + 1 rel points (x 0, y 0 ), (x 1, y 1 ),..., (x N, y N ), with x

More information

GENERALIZATIONS OF WEIGHTED TRAPEZOIDAL INEQUALITY FOR MONOTONIC MAPPINGS AND ITS APPLICATIONS. (b a)3 [f(a) + f(b)] f x (a,b)

GENERALIZATIONS OF WEIGHTED TRAPEZOIDAL INEQUALITY FOR MONOTONIC MAPPINGS AND ITS APPLICATIONS. (b a)3 [f(a) + f(b)] f x (a,b) GENERALIZATIONS OF WEIGHTED TRAPEZOIDAL INEQUALITY FOR MONOTONIC MAPPINGS AND ITS APPLICATIONS KUEI-LIN TSENG, GOU-SHENG YANG, AND SEVER S. DRAGOMIR Abstrct. In this pper, we estblish some generliztions

More information

The Algebra (al-jabr) of Matrices

The Algebra (al-jabr) of Matrices Section : Mtri lgebr nd Clculus Wshkewicz College of Engineering he lgebr (l-jbr) of Mtrices lgebr s brnch of mthemtics is much broder thn elementry lgebr ll of us studied in our high school dys. In sense

More information

The Riemann Integral

The Riemann Integral Deprtment of Mthemtics King Sud University 2017-2018 Tble of contents 1 Anti-derivtive Function nd Indefinite Integrls 2 3 4 5 Indefinite Integrls & Anti-derivtive Function Definition Let f : I R be function

More information

Riemann Sums and Riemann Integrals

Riemann Sums and Riemann Integrals Riemnn Sums nd Riemnn Integrls Jmes K. Peterson Deprtment of Biologicl Sciences nd Deprtment of Mthemticl Sciences Clemson University August 26, 2013 Outline 1 Riemnn Sums 2 Riemnn Integrls 3 Properties

More information

Advanced Calculus: MATH 410 Notes on Integrals and Integrability Professor David Levermore 17 October 2004

Advanced Calculus: MATH 410 Notes on Integrals and Integrability Professor David Levermore 17 October 2004 Advnced Clculus: MATH 410 Notes on Integrls nd Integrbility Professor Dvid Levermore 17 October 2004 1. Definite Integrls In this section we revisit the definite integrl tht you were introduced to when

More information

13.3 CLASSICAL STRAIGHTEDGE AND COMPASS CONSTRUCTIONS

13.3 CLASSICAL STRAIGHTEDGE AND COMPASS CONSTRUCTIONS 33 CLASSICAL STRAIGHTEDGE AND COMPASS CONSTRUCTIONS As simple ppliction of the results we hve obtined on lgebric extensions, nd in prticulr on the multiplictivity of extension degrees, we cn nswer (in

More information

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

More information

Riemann Sums and Riemann Integrals

Riemann Sums and Riemann Integrals Riemnn Sums nd Riemnn Integrls Jmes K. Peterson Deprtment of Biologicl Sciences nd Deprtment of Mthemticl Sciences Clemson University August 26, 203 Outline Riemnn Sums Riemnn Integrls Properties Abstrct

More information

Integration Techniques

Integration Techniques Integrtion Techniques. Integrtion of Trigonometric Functions Exmple. Evlute cos x. Recll tht cos x = cos x. Hence, cos x Exmple. Evlute = ( + cos x) = (x + sin x) + C = x + 4 sin x + C. cos 3 x. Let u

More information

FUZZY HOMOTOPY CONTINUATION METHOD FOR SOLVING FUZZY NONLINEAR EQUATIONS

FUZZY HOMOTOPY CONTINUATION METHOD FOR SOLVING FUZZY NONLINEAR EQUATIONS VOL NO 6 AUGUST 6 ISSN 89-668 6-6 Asin Reserch Publishing Networ (ARPN) All rights reserved wwwrpnjournlscom FUZZY HOMOTOPY CONTINUATION METHOD FOR SOLVING FUZZY NONLINEAR EQUATIONS Muhmmd Zini Ahmd Nor

More information

38 Riemann sums and existence of the definite integral.

38 Riemann sums and existence of the definite integral. 38 Riemnn sums nd existence of the definite integrl. In the clcultion of the re of the region X bounded by the grph of g(x) = x 2, the x-xis nd 0 x b, two sums ppered: ( n (k 1) 2) b 3 n 3 re(x) ( n These

More information

A New Grey-rough Set Model Based on Interval-Valued Grey Sets

A New Grey-rough Set Model Based on Interval-Valued Grey Sets Proceedings of the 009 IEEE Interntionl Conference on Systems Mn nd Cybernetics Sn ntonio TX US - October 009 New Grey-rough Set Model sed on Intervl-Vlued Grey Sets Wu Shunxing Deprtment of utomtion Ximen

More information

Exam 2, Mathematics 4701, Section ETY6 6:05 pm 7:40 pm, March 31, 2016, IH-1105 Instructor: Attila Máté 1

Exam 2, Mathematics 4701, Section ETY6 6:05 pm 7:40 pm, March 31, 2016, IH-1105 Instructor: Attila Máté 1 Exm, Mthemtics 471, Section ETY6 6:5 pm 7:4 pm, Mrch 1, 16, IH-115 Instructor: Attil Máté 1 17 copies 1. ) Stte the usul sufficient condition for the fixed-point itertion to converge when solving the eqution

More information

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations.

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations. Lecture 3 3 Solving liner equtions In this lecture we will discuss lgorithms for solving systems of liner equtions Multiplictive identity Let us restrict ourselves to considering squre mtrices since one

More information

A MEAN VALUE THEOREM FOR GENERALIZED RIEMANN DERIVATIVES. 1. Introduction Throughout this article, will denote the following functional difference:

A MEAN VALUE THEOREM FOR GENERALIZED RIEMANN DERIVATIVES. 1. Introduction Throughout this article, will denote the following functional difference: PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volme 136, Nmber 2, Febrry 200, Pges 569 576 S 0002-9939(07)0976-9 Article electroniclly pblished on November 6, 2007 A MEAN VALUE THEOREM FOR GENERALIZED

More information

Orthogonal Polynomials

Orthogonal Polynomials Mth 4401 Gussin Qudrture Pge 1 Orthogonl Polynomils Orthogonl polynomils rise from series solutions to differentil equtions, lthough they cn be rrived t in vriety of different mnners. Orthogonl polynomils

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

Convex Sets and Functions

Convex Sets and Functions B Convex Sets nd Functions Definition B1 Let L, +, ) be rel liner spce nd let C be subset of L The set C is convex if, for ll x,y C nd ll [, 1], we hve 1 )x+y C In other words, every point on the line

More information

Acceptance Sampling by Attributes

Acceptance Sampling by Attributes Introduction Acceptnce Smpling by Attributes Acceptnce smpling is concerned with inspection nd decision mking regrding products. Three spects of smpling re importnt: o Involves rndom smpling of n entire

More information

Midpoint Approximation

Midpoint Approximation Midpoint Approximtion Sometimes, we need to pproximte n integrl of the form R b f (x)dx nd we cnnot find n ntiderivtive in order to evlute the integrl. Also we my need to evlute R b f (x)dx where we do

More information

Chapter 5 Bending Moments and Shear Force Diagrams for Beams

Chapter 5 Bending Moments and Shear Force Diagrams for Beams Chpter 5 ending Moments nd Sher Force Digrms for ems n ddition to illy loded brs/rods (e.g. truss) nd torsionl shfts, the structurl members my eperience some lods perpendiculr to the is of the bem nd will

More information

Week 10: Line Integrals

Week 10: Line Integrals Week 10: Line Integrls Introduction In this finl week we return to prmetrised curves nd consider integrtion long such curves. We lredy sw this in Week 2 when we integrted long curve to find its length.

More information

Review of Riemann Integral

Review of Riemann Integral 1 Review of Riemnn Integrl In this chpter we review the definition of Riemnn integrl of bounded function f : [, b] R, nd point out its limittions so s to be convinced of the necessity of more generl integrl.

More information

Math 113 Fall Final Exam Review. 2. Applications of Integration Chapter 6 including sections and section 6.8

Math 113 Fall Final Exam Review. 2. Applications of Integration Chapter 6 including sections and section 6.8 Mth 3 Fll 0 The scope of the finl exm will include: Finl Exm Review. Integrls Chpter 5 including sections 5. 5.7, 5.0. Applictions of Integrtion Chpter 6 including sections 6. 6.5 nd section 6.8 3. Infinite

More information

f(x) dx, If one of these two conditions is not met, we call the integral improper. Our usual definition for the value for the definite integral

f(x) dx, If one of these two conditions is not met, we call the integral improper. Our usual definition for the value for the definite integral Improper Integrls Every time tht we hve evluted definite integrl such s f(x) dx, we hve mde two implicit ssumptions bout the integrl:. The intervl [, b] is finite, nd. f(x) is continuous on [, b]. If one

More information

1.2. Linear Variable Coefficient Equations. y + b "! = a y + b " Remark: The case b = 0 and a non-constant can be solved with the same idea as above.

1.2. Linear Variable Coefficient Equations. y + b ! = a y + b  Remark: The case b = 0 and a non-constant can be solved with the same idea as above. 1 12 Liner Vrible Coefficient Equtions Section Objective(s): Review: Constnt Coefficient Equtions Solving Vrible Coefficient Equtions The Integrting Fctor Method The Bernoulli Eqution 121 Review: Constnt

More information