g(y(a), y(b)) = o, B a y(a)+b b y(b)=c, Boundary Value Problems Lecture Notes to Accompany
|
|
- Jason Harrison
- 8 years ago
- Views:
Transcription
1 Lecture Notes to Accompny Scientific Computing An Introductory Survey Second Edition by Michel T Heth Boundry Vlue Problems Side conditions prescribing solution or derivtive vlues t specified points required to mke solution of ODE unique In initil vlue problem ll side conditions specified t single point sy t Chpter Boundry Vlue Problems for Ordinry Differentil Equtions In boundry vlue problem (BVP) side conditions specified t more thn one point kth order ODE or equivlent first-order system requires k side conditions Copyright c 2 Reproduction permitted only for noncommercil eductionl use in conjunction with the book For ODE side conditions typiclly specified t two points endpoints of intervl [ b] so we hve two-point boundry vlue problem 2 Boundry Vlue Problems continued Generl first-order two-point BVP hs form y f(t y) <t<b with boundry conditions Exmple: Seprted Liner BC Two-point BVP for second-order sclr ODE g(y() y(b)) o where f: R n R n nd g: R 2n R n u f(t u u ) with boundry conditions <t<b Boundry conditions re seprted if ny given component of g involves solution vlues only t or t b but not both Boundry conditions re liner if of form B y()b b y(b)c where B B b R n n nd c R n u() α u(b) β is equivlent to first-order system of ODEs [ ] y y y 2 2 <t<b f(t y y 2 ) with seprted liner boundry conditions y () y (b) α y 2 () y 2 (b) β BVP is liner if both ODE nd boundry conditions re liner 3 4
2 Existence nd Uniqueness Unlike IVP with BVP we cnnot begin t initil point nd continue solution step by step to nerby points Insted solution determined everywhere simultneously so existence nd/or uniqueness my not hold For exmple u u with boundry conditions u() <t<b u(b)β with b integer multiple of π hs infinitely mny solutions if β but no solution if β Existence nd Uniqueness continued In generl solvbility of BVP y f(t y) with boundry conditions <t<b g(y() y(b)) o depends on solvbility of lgebric eqution g(x y(b; x)) o where y(t; x) denotes solution to ODE with initil condition y() xfor x R n Solvbility of ltter system is difficult to estblish if g is nonliner 5 6 Existence nd Uniqueness continued For liner BVP existence nd uniqueness re more trctble Consider liner BVP y A(t) y b(t) <t<b where A(t) nd b(t) re continuous with boundry conditions B y()b b y(b)c Let Y (t) denote mtrix whose ith column y i (t) clled ith mode is solution to y A(t)y with initil condition y() e i Then BVP hs unique solution if nd only if mtrix Q B Y ()B b Y(b) is nonsingulr 7 Existence nd Uniqueness continued Assuming Q is nonsingulr define Φ(t) Y(t)Q nd Green s function { Φ(t)B Φ()Φ G(t s) (s) s t Φ(t)B b Φ(b)Φ (s) t<s b Then solution to BVP given by y(t) Φ(t)c G(t s) b(s) ds This result lso gives bsolute condition number for BVP κ mx{ Φ G } 8
3 Conditioning nd Stbility Conditioning or stbility of BVP depends on interply between growth of solution modes nd boundry conditions For IVP instbility is ssocited with modes tht grow exponentilly s time increses For BVP solution is determined everywhere simultneously so there is no notion of direction of integrtion in intervl [ b] Growth of modes incresing with time is limited by boundry conditions t b nd growth of decying modes is limited by boundry conditions t Numericl Methods for BVPs For IVP initil dt supply ll informtion necessry to begin numericl solution method t initil point nd step forwrd from there For BVP we hve insufficient informtion to begin step-by-step numericl method so numericl methods for solving BVPs re more complicted thn those for solving IVPs We consider four types of numericl methods for two-point BVPs: Shooting Finite difference For BVP to be well-conditioned growing nd decying modes must be controlled ppropritely by boundry conditions imposed 9 Colloction Glerkin Shooting Method In sttement of two-point BVP we re given vlue of u() Shooting Method continued If we lso knew vlue of u () then we would hve IVP tht we could solve by methods previously discussed Lcking tht informtion we try sequence of incresingly ccurte guesses until we find vlue for u () such tht when we solve resulting IVP pproximte solution vlue t t b mtches desired boundry vlue u(b) β α β b For given γ vlue t b of solution u(b) toivp with initil conditions u() α u f(t u u ) u () γ cn be considered s function of γ syg(γ) Then BVP becomes problem of solving eqution g(γ) β One-dimensionl zero finder cn be used to solve this sclr eqution 2
4 Exmple: Shooting Method Consider two-point BVP for second-order ODE u 6t <t< u() u() For ech guess for u () we integrte ODE using clssicl fourth-order Runge-Kutt method to determine how close we come to hitting desired solution vlue t t We trnsform second-order ODE into system of two first-order ODEs y y2 y 2 6t We try initil slope of y 2 () Using step size h 5 we first step from t tot 5 Clssicl fourth-order Runge-Kutt method gives pproximte solution vlue t t y () y () h 6 (k k 2 k 3 k 4 ) ( ) Next we step from t 5tot 2 getting y (2) ( ) so we hve hit y () 2 insted of desired vlue y () We try gin this time with initil slope y 2 () obtining y () 5 ( ) y (2) ( 25 3 ) so we hve hit y () insted of desired vlue y () We now hve initil slope brcketed between nd We omit further itertions necessry to identify correct initil slope which turns out to be y 2 () : y () ( )
5 y (2) ( 75 3 ) so we hve indeed hit trget solution vlue y () st ttempt trget 2nd ttempt 5 Multiple Shooting Simple shooting method inherits stbility (or instbility) ssocited IVP which my be unstble even when BVP is stble Such ill-conditioning my mke it difficult to chieve convergence of itertive method for solving nonliner eqution Potentil remedy is multiple shooting in which intervl [ b] is divided into subintervls nd shooting is crried out on ech Requiring continuity t internl mesh points provides BC for individul subproblems Multiple shooting results in lrger system of nonliner equtions to solve 7 8 Finite Difference Method Finite difference method converts BVP into system of lgebric equtions by replcing ll derivtives by finite difference pproximtions For exmple to solve two-point BVP u f(t u u ) u() α <t<b u(b) β we introduce mesh points t i ih i n where h (b )/(n) We lredy hve y u() αnd y n u(b) β nd we seek pproximte solution vlue y i u(t i ) t ech mesh point t i i n Finite Difference Method continued We replce derivtives by finite difference quotients such s nd u (t i ) y i y i 2h u (t i ) y i 2y i y i h 2 yielding system of equtions ( y i 2y i y i h 2 f t i y i y ) i y i 2h to be solved for unknowns y i i n System of equtions my be liner or nonliner depending on whether f is liner or nonliner 9 2
6 Exmple: Finite Difference Method Consider two-point BVP Finite Difference Method continued u 6t <t< In this exmple system to be solved is tridigonl which sves on both work nd storge compred to generl system of equtions This is generlly true of finite difference methods: they yield sprse systems becuse ech eqution involves few vribles u() u() To keep computtion to minimum we compute pproximte solution t one mesh point in intervl [ ] t 5 Including boundry points we hve three mesh points t t 5 nd t 2 From BC we know tht y u(t ) nd y 2 u(t 2 ) nd we seek pproximte solution y u(t ) 2 22 Approximting second derivtive by stndrd finite difference quotient t t gives eqution ( y 2 2y y h 2 f t y y ) 2 y 2h Substituting boundry dt mesh size nd right hnd side for this exmple 2y (5) 2 6t or so tht 4 8y 6(5) 3 In prcticl problem much smller step size nd mny more mesh points would be required to chieve cceptble ccurcy We would therefore obtin system of equtions to solve for pproximte solution vlues t mesh points rther thn single eqution s in this exmple y(5) y /825 which grees with pproximte solution t t 5 tht we previously computed by shooting method 23 24
7 Colloction Method Colloction method pproximtes solution to BVP by finite liner combintion of bsis functions For two-point BVP u f(t u u ) <t<b u() α u(b) β we seek pproximte solution of form n u(t) v(t x) x i φ i (t) i where φ i re bsis functions defined on [ b] nd x is n-vector of prmeters to be determined Colloction Method Populr choices of bsis functions include polynomils B-splines nd trigonometric functions Bsis functions with globl support such s polynomils or trigonometric functions yield spectrl or pseudospectrl method Bsis functions with highly loclized support such s B-splines yield finite element method Exmple: Colloction Method Colloction Method continued Consider gin two-point BVP To determine vector of prmeters x define set of n colloction points t < < t n b t which pproximte solution v(t x) is forced to stisfy ODE nd boundry conditions u 6t <t< u() u() Common choices of colloction points include eqully-spced mesh or Chebyshev points Suitbly smooth bsis functions cn be differentited nlyticlly so tht pproximte solution nd its derivtives cn be substituted into ODE nd BC to obtin system of lgebric equtions for unknown prmeters x To keep computtion to minimum we use one interior colloction point t 5 Including boundry points we hve three colloction points t t 5 nd t 2 so we will be ble to determine three prmeters As bsis functions we use first three monomils so pproximte solution hs form v(t x) x x 2 tx 3 t
8 Derivtives of pproximte solution function with respect to t re given by v (t x) x 2 x 3 t v (t x) 2x 3 Requiring ODE to be stisfied t interior colloction point t 2 5 gives eqution or v (t 2 x) f(t 2 v(t 2 x)v (t 2 x)) 2x 3 6t 2 6(5) 3 Left boundry condition t t gives eqution x x 2 t x 3 t 2 x nd right boundry condition t t 3 gives eqution x x 2 t 3 x 3 t 2 3 x x 2 x 3 29 Solving this system of three equtions in three unknowns gives x x 2 5 x 3 5 so pproximte solution function is qudrtic polynomil u(t) v(t x) 5t5t 2 At interior colloction point t 2 5 we hve pproximte solution vlue u(5) v(5 x) 25 which grees with solution vlue t t 5 obtined previously by other two methods Glerkin Method Rther thn forcing residul to be zero t finite number of points s in colloction we could insted minimize residul over entire intervl of integrtion For exmple for sclr Poisson eqution in one dimension u f(t) <t<b with homogeneous boundry conditions u() u(b) subsitute pproximte solution n u(t) v(t x) x i φ i (t) i into ODE nd define residul r(t x) v n (t x) f(t) x i φ i (t) f(t) i 3 Glerkin Method continued Using lest squres method we cn minimize F (x) 2 r(t x)2 dt by setting ech component of its grdient to zero which yields symmetric system of liner lgebric equtions Ax b where ij φ j (t)φ i (t) dt nd b i f(t)φ i (t) dt whose solution gives vector of prmeters x More generlly weighted residul method forces residul to be orthogonl to ech of set of weight functions or test functions w i ie r(t x)w i(t) dt i n which yields liner system Ax b where now ij φ j (t)w i(t) dt nd b i i(t) dt whose solution gives vector of prmeters x 32
9 Glerkin Method continued Glerkin Method continued Mtrix resulting from weighted residul method is generlly not symmetric nd its entries involve second derivtives of bsis functions Both drwbcks overcome by Glerkin method in which weight functions re chosen to be sme s bsis functions ie w i φ i i n Orthogonlity condition then becomes r(t x)φ i(t) dt i n or v (t x)φ i (t) dt i(t) dt i n 33 Degree of differentibility cn be reduced using integrtion by prts which gives v (t x)φ i (t) dt v (t)φ i (t) b v (t)φ i (t) dt v (b)φ i (b) v ()φ i () v (t)φ i (t) dt Assuming bsis functions φ i stisfy homogeneous boundry conditions so φ i () φ i () orthogonlity condition then becomes v (t)φ i (t) dt i(t) dt i n which yields system of liner equtions Ax b with ij φ j (t)φ i (t) dt nd b i i(t) dt whose solution gives vector of prmeters x A is symmetric nd involves only first derivtives of bsis functions 34 Exmple: Glerkin Method Consider gin two-point BVP u 6t <t< u() u() Thus we seek pproximte solution of form u(t) v(t x) x φ (t)x 2 φ 2 (t)x 3 φ 3 (t) We will pproximte solution by piecewise liner polynomil for which B-splines of degree ( ht functions) form suitble set of bsis functions To keep computtion to minimum we gin use sme three mesh points but now they become knots in piecewise liner polynomil pproximtion φ 5 φ 2 5 φ From BC we must hve x nd x 3 To determine remining prmeter x 2 we impose Glerkin orthogonlity condition on interior bsis function φ 2 nd obtin eqution ( 3 ) j φ j (t)φ 2 (t) dt x j 6tφ 2(t) dt or upon evluting these simple integrls nlyticlly 2x 4x 2 x 3 3/2 36
10 Substituting known vlues for x nd x 3 then gives x 2 /8 for remining unknown prmeter so piecewise liner pproximte solution is u(t) v(t x) 25φ 2 (t)φ 3 (t) 5 5 We note tht v(5 x) 25 which gin is exct for this prticulr problem More relistic problem would hve mny more interior mesh points nd bsis functions nd correspondingly mny prmeters to be determined Resulting system of equtions would be much lrger but still sprse nd therefore reltively esy to solve provided locl bsis functions such s ht functions re used Resulting pproximte solution function is less smooth thn true solution but becomes more ccurte s more mesh points re used Eigenvlue Problems Stndrd eigenvlue problem for second-order ODE hs form u λf(t u u ) u() α <t<b u(b) β where we seek not only solution u but lso prmeter λ s well Sclr λ (possibly complex) is eigenvlue nd solution u corresponding eigenfunction for this two-point BVP Discretiztion of eigenvlue problem for ODE results in lgebric eigenvlue problem whose solution pproximtes tht of originl problem Exmple: Eigenvlue Problem Consider liner two-point BVP u λg(t)u < t < b u() u(b) Introduce discrete mesh points t i in intervl [ b] with mesh spcing h nd use stndrd finite difference pproximtion for second derivtive to obtin lgebric system y i 2y i y i h 2 λg i y i i n where y i u(t i ) nd g i g(t i ) nd from BC y u() nd y n u(b) 39 4
11 Assuming g i divide eqution i by g i for i n to obtin liner system Ay λy where n n mtrix A hs tridigonl form 2/g /g A /g 2 2/g 2 /g 2 h 2 /g n 2/g n /g n /g n 2/g n This stndrd lgebric eigenvlue problem cn be solved by methods discussed previously 4
Lecture Notes to Accompany. Scientific Computing An Introductory Survey. by Michael T. Heath. Chapter 10
Lecture Notes to Accompany Scientific Computing An Introductory Survey Second Edition by Michael T. Heath Chapter 10 Boundary Value Problems for Ordinary Differential Equations Copyright c 2001. Reproduction
More informationand thus, they are similar. If k = 3 then the Jordan form of both matrices is
Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If
More informationPolynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )
Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +
More informationFactoring Polynomials
Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles
More informationMODULE 3. 0, y = 0 for all y
Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)
More informationLINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES
LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of
More informationReview guide for the final exam in Math 233
Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered
More informationGraphs on Logarithmic and Semilogarithmic Paper
0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl
More information4.11 Inner Product Spaces
314 CHAPTER 4 Vector Spces 9. A mtrix of the form 0 0 b c 0 d 0 0 e 0 f g 0 h 0 cnnot be invertible. 10. A mtrix of the form bc d e f ghi such tht e bd = 0 cnnot be invertible. 4.11 Inner Product Spces
More informationVectors 2. 1. Recap of vectors
Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms
More informationThe Velocity Factor of an Insulated Two-Wire Transmission Line
The Velocity Fctor of n Insulted Two-Wire Trnsmission Line Problem Kirk T. McDonld Joseph Henry Lbortories, Princeton University, Princeton, NJ 08544 Mrch 7, 008 Estimte the velocity fctor F = v/c nd the
More informationLectures 8 and 9 1 Rectangular waveguides
1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves
More informationExample A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding
1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde
More informationAll pay auctions with certain and uncertain prizes a comment
CENTER FOR RESEARC IN ECONOMICS AND MANAGEMENT CREAM Publiction No. 1-2015 All py uctions with certin nd uncertin prizes comment Christin Riis All py uctions with certin nd uncertin prizes comment Christin
More informationMath 135 Circles and Completing the Square Examples
Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for
More informationSection 7-4 Translation of Axes
62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the
More informationA new generalized Jacobi Galerkin operational matrix of derivatives: two algorithms for solving fourth-order boundary value problems
Abd-Elhmeed et l. Advnces in Difference Equtions (2016) 2016:22 DOI 10.1186/s13662-016-0753-2 R E S E A R C H Open Access A new generlized Jcobi Glerkin opertionl mtrix of derivtives: two lgorithms for
More informationCHAPTER 11 Numerical Differentiation and Integration
CHAPTER 11 Numericl Differentition nd Integrtion Differentition nd integrtion re bsic mthemticl opertions with wide rnge of pplictions in mny res of science. It is therefore importnt to hve good methods
More informationEuler Euler Everywhere Using the Euler-Lagrange Equation to Solve Calculus of Variation Problems
Euler Euler Everywhere Using the Euler-Lgrnge Eqution to Solve Clculus of Vrition Problems Jenine Smllwood Principles of Anlysis Professor Flschk My 12, 1998 1 1. Introduction Clculus of vritions is brnch
More information9 CONTINUOUS DISTRIBUTIONS
9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete
More information5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.
5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued
More informationLecture 3 Gaussian Probability Distribution
Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike
More informationExample 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.
2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this
More informationBabylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity
Bbylonin Method of Computing the Squre Root: Justifictions Bsed on Fuzzy Techniques nd on Computtionl Complexity Olg Koshelev Deprtment of Mthemtics Eduction University of Texs t El Pso 500 W. University
More informationIntegration. 148 Chapter 7 Integration
48 Chpter 7 Integrtion 7 Integrtion t ech, by supposing tht during ech tenth of second the object is going t constnt speed Since the object initilly hs speed, we gin suppose it mintins this speed, but
More informationSmall Business Networking
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology
More informationPROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY
MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive
More informationSPECIAL PRODUCTS AND FACTORIZATION
MODULE - Specil Products nd Fctoriztion 4 SPECIAL PRODUCTS AND FACTORIZATION In n erlier lesson you hve lernt multipliction of lgebric epressions, prticulrly polynomils. In the study of lgebr, we come
More informationReasoning to Solve Equations and Inequalities
Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing
More informationEQUATIONS OF LINES AND PLANES
EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint
More information9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes
The Sclr Product 9.3 Introduction There re two kinds of multipliction involving vectors. The first is known s the sclr product or dot product. This is so-clled becuse when the sclr product of two vectors
More informationMathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100
hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by
More informationUse Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.
Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd
More informationRIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS
RIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS Known for over 500 yers is the fct tht the sum of the squres of the legs of right tringle equls the squre of the hypotenuse. Tht is +b c. A simple proof is
More informationSmall Business Networking
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology
More information15.6. The mean value and the root-mean-square value of a function. Introduction. Prerequisites. Learning Outcomes. Learning Style
The men vlue nd the root-men-squre vlue of function 5.6 Introduction Currents nd voltges often vry with time nd engineers my wish to know the verge vlue of such current or voltge over some prticulr time
More informationWarm-up for Differential Calculus
Summer Assignment Wrm-up for Differentil Clculus Who should complete this pcket? Students who hve completed Functions or Honors Functions nd will be tking Differentil Clculus in the fll of 015. Due Dte:
More informationHarvard College. Math 21a: Multivariable Calculus Formula and Theorem Review
Hrvrd College Mth 21: Multivrible Clculus Formul nd Theorem Review Tommy McWillim, 13 tmcwillim@college.hrvrd.edu December 15, 2009 1 Contents Tble of Contents 4 9 Vectors nd the Geometry of Spce 5 9.1
More informationModule Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials
MEI Mthemtics in Ection nd Instry Topic : Proof MEI Structured Mthemtics Mole Summry Sheets C, Methods for Anced Mthemtics (Version B reference to new book) Topic : Nturl Logrithms nd Eponentils Topic
More informationQUADRATURE METHODS. July 19, 2011. Kenneth L. Judd. Hoover Institution
QUADRATURE METHODS Kenneth L. Judd Hoover Institution July 19, 2011 1 Integrtion Most integrls cnnot be evluted nlyticlly Integrls frequently rise in economics Expected utility Discounted utility nd profits
More informationTITLE THE PRINCIPLES OF COIN-TAP METHOD OF NON-DESTRUCTIVE TESTING
TITLE THE PRINCIPLES OF COIN-TAP METHOD OF NON-DESTRUCTIVE TESTING Sung Joon Kim*, Dong-Chul Che Kore Aerospce Reserch Institute, 45 Eoeun-Dong, Youseong-Gu, Dejeon, 35-333, Kore Phone : 82-42-86-231 FAX
More informationCURVES ANDRÉ NEVES. that is, the curve α has finite length. v = p q p q. a i.e., the curve of smallest length connecting p to q is a straight line.
CURVES ANDRÉ NEVES 1. Problems (1) (Ex 1 of 1.3 of Do Crmo) Show tht the tngent line to the curve α(t) (3t, 3t 2, 2t 3 ) mkes constnt ngle with the line z x, y. (2) (Ex 6 of 1.3 of Do Crmo) Let α(t) (e
More informationSmall Business Networking
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology
More informationLecture 5. Inner Product
Lecture 5 Inner Product Let us strt with the following problem. Given point P R nd line L R, how cn we find the point on the line closest to P? Answer: Drw line segment from P meeting the line in right
More informationMATH 150 HOMEWORK 4 SOLUTIONS
MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive
More informationSmall Business Networking
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology
More informationwww.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values)
www.mthsbo.org.uk CORE SUMMARY NOTES Functions A function is rule which genertes ectl ONE OUTPUT for EVERY INPUT. To be defined full the function hs RULE tells ou how to clculte the output from the input
More information6.2 Volumes of Revolution: The Disk Method
mth ppliction: volumes of revolution, prt ii Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem ) nd the ccumultion process is to determine so-clled volumes of
More informationHow To Network A Smll Business
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology
More information1. Find the zeros Find roots. Set function = 0, factor or use quadratic equation if quadratic, graph to find zeros on calculator
AP Clculus Finl Review Sheet When you see the words. This is wht you think of doing. Find the zeros Find roots. Set function =, fctor or use qudrtic eqution if qudrtic, grph to find zeros on clcultor.
More informationIntegration by Substitution
Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is
More informationOperations with Polynomials
38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: Write polynomils in stndrd form nd identify the leding coefficients nd degrees of polynomils Add nd subtrct polynomils Multiply
More information4 Approximations. 4.1 Background. D. Levy
D. Levy 4 Approximtions 4.1 Bckground In this chpter we re interested in pproximtion problems. Generlly speking, strting from function f(x) we would like to find different function g(x) tht belongs to
More informationBinary Representation of Numbers Autar Kaw
Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy
More informationReview Problems for the Final of Math 121, Fall 2014
Review Problems for the Finl of Mth, Fll The following is collection of vrious types of smple problems covering sections.,.5, nd.7 6.6 of the text which constitute only prt of the common Mth Finl. Since
More informationCOMPARISON OF SOME METHODS TO FIT A MULTIPLICATIVE TARIFF STRUCTURE TO OBSERVED RISK DATA BY B. AJNE. Skandza, Stockholm ABSTRACT
COMPARISON OF SOME METHODS TO FIT A MULTIPLICATIVE TARIFF STRUCTURE TO OBSERVED RISK DATA BY B. AJNE Skndz, Stockholm ABSTRACT Three methods for fitting multiplictive models to observed, cross-clssified
More information2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration
Source: http://www.mth.cuhk.edu.hk/~mt26/mt26b/notes/notes3.pdf 25-6 Second Term MAT26B 1 Supplementry Notes 3 Interchnge of Differentition nd Integrtion The theme of this course is bout vrious limiting
More informationKarlstad University. Division for Engineering Science, Physics and Mathematics. Yury V. Shestopalov and Yury G. Smirnov. Integral Equations
Krlstd University Division for Engineering Science, Physics nd Mthemtics Yury V. Shestoplov nd Yury G. Smirnov Integrl Equtions A compendium Krlstd Contents 1 Prefce 4 Notion nd exmples of integrl equtions
More informationPhysics 43 Homework Set 9 Chapter 40 Key
Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x
More informationEcon 4721 Money and Banking Problem Set 2 Answer Key
Econ 472 Money nd Bnking Problem Set 2 Answer Key Problem (35 points) Consider n overlpping genertions model in which consumers live for two periods. The number of people born in ech genertion grows in
More informationFUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation
FUNCTIONS AND EQUATIONS. SETS AND SUBSETS.. Definition of set. A set is ny collection of objects which re clled its elements. If x is n element of the set S, we sy tht x belongs to S nd write If y does
More informationModule 2. Analysis of Statically Indeterminate Structures by the Matrix Force Method. Version 2 CE IIT, Kharagpur
Module Anlysis of Stticlly Indeterminte Structures by the Mtrix Force Method Version CE IIT, Khrgpur esson 9 The Force Method of Anlysis: Bems (Continued) Version CE IIT, Khrgpur Instructionl Objectives
More informationExperiment 6: Friction
Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht
More information6 Energy Methods And The Energy of Waves MATH 22C
6 Energy Methods And The Energy of Wves MATH 22C. Conservtion of Energy We discuss the principle of conservtion of energy for ODE s, derive the energy ssocited with the hrmonic oscilltor, nd then use this
More informationTreatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.
The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only
More informationAREA OF A SURFACE OF REVOLUTION
AREA OF A SURFACE OF REVOLUTION h cut r πr h A surfce of revolution is formed when curve is rotted bout line. Such surfce is the lterl boundr of solid of revolution of the tpe discussed in Sections 7.
More informationRoots of Polynomials. Ch. 7. Roots of Polynomials. Roots of Polynomials. dy dt. a dt. y = General form:
Roots o Polynomils C. 7 Generl orm: Roots o Polynomils ( ) n n order o te polynomil i constnt coeicients n Roots Rel or Comple. For n n t order polynomil n rel or comple roots. I n is odd At lest rel root
More informationPure C4. Revision Notes
Pure C4 Revision Notes Mrch 0 Contents Core 4 Alger Prtil frctions Coordinte Geometry 5 Prmetric equtions 5 Conversion from prmetric to Crtesin form 6 Are under curve given prmetriclly 7 Sequences nd
More informationNumerical Methods of Approximating Definite Integrals
6 C H A P T E R Numericl Methods o Approimting Deinite Integrls 6. APPROXIMATING SUMS: L n, R n, T n, AND M n Introduction Not only cn we dierentite ll the bsic unctions we ve encountered, polynomils,
More informationCOMPONENTS: COMBINED LOADING
LECTURE COMPONENTS: COMBINED LOADING Third Edition A. J. Clrk School of Engineering Deprtment of Civil nd Environmentl Engineering 24 Chpter 8.4 by Dr. Ibrhim A. Asskkf SPRING 2003 ENES 220 Mechnics of
More informationINTERCHANGING TWO LIMITS. Zoran Kadelburg and Milosav M. Marjanović
THE TEACHING OF MATHEMATICS 2005, Vol. VIII, 1, pp. 15 29 INTERCHANGING TWO LIMITS Zorn Kdelburg nd Milosv M. Mrjnović This pper is dedicted to the memory of our illustrious professor of nlysis Slobodn
More informationThe Definite Integral
Chpter 4 The Definite Integrl 4. Determining distnce trveled from velocity Motivting Questions In this section, we strive to understnd the ides generted by the following importnt questions: If we know
More informationHow To Understand The Theory Of Inequlities
Ostrowski Type Inequlities nd Applictions in Numericl Integrtion Edited By: Sever S Drgomir nd Themistocles M Rssis SS Drgomir) School nd Communictions nd Informtics, Victori University of Technology,
More informationHow To Set Up A Network For Your Business
Why Network is n Essentil Productivity Tool for Any Smll Business TechAdvisory.org SME Reports sponsored by Effective technology is essentil for smll businesses looking to increse their productivity. Computer
More informationHelicopter Theme and Variations
Helicopter Theme nd Vritions Or, Some Experimentl Designs Employing Pper Helicopters Some possible explntory vribles re: Who drops the helicopter The length of the rotor bldes The height from which the
More informationRedistributing the Gains from Trade through Non-linear. Lump-sum Transfers
Redistributing the Gins from Trde through Non-liner Lump-sum Trnsfers Ysukzu Ichino Fculty of Economics, Konn University April 21, 214 Abstrct I exmine lump-sum trnsfer rules to redistribute the gins from
More informationLinear Equations in Two Variables
Liner Equtions in Two Vribles In this chpter, we ll use the geometry of lines to help us solve equtions. Liner equtions in two vribles If, b, ndr re rel numbers (nd if nd b re not both equl to 0) then
More informationMath 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.
Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose
More informationThinking out of the Box... Problem It s a richer problem than we ever imagined
From the Mthemtics Techer, Vol. 95, No. 8, pges 568-574 Wlter Dodge (not pictured) nd Steve Viktor Thinking out of the Bo... Problem It s richer problem thn we ever imgined The bo problem hs been stndrd
More informationOn the degrees of freedom in GR
On the degrees of freedom in GR István Rácz Wigner RCP Budpest rcz.istvn@wigner.mt.hu University of the Bsque Country Bilbo, 27 My, 2015 István Rácz (Wigner RCP, Budpest) degrees of freedom 27 My, 2015
More informationAppendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:
Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you
More informationBasic Analysis of Autarky and Free Trade Models
Bsic Anlysis of Autrky nd Free Trde Models AUTARKY Autrky condition in prticulr commodity mrket refers to sitution in which country does not engge in ny trde in tht commodity with other countries. Consequently
More informationDesign Example 1 Special Moment Frame
Design Exmple 1 pecil Moment Frme OVERVIEW tructurl steel specil moment frmes (MF) re typiclly comprised of wide-flnge bems, columns, nd bem-column connections. Connections re proportioned nd detiled to
More informationThe invention of line integrals is motivated by solving problems in fluid flow, forces, electricity and magnetism.
Instrutor: Longfei Li Mth 43 Leture Notes 16. Line Integrls The invention of line integrls is motivted by solving problems in fluid flow, fores, eletriity nd mgnetism. Line Integrls of Funtion We n integrte
More informationBayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom
Byesin Updting with Continuous Priors Clss 3, 8.05, Spring 04 Jeremy Orloff nd Jonthn Bloom Lerning Gols. Understnd prmeterized fmily of distriutions s representing continuous rnge of hypotheses for the
More informationSmall Businesses Decisions to Offer Health Insurance to Employees
Smll Businesses Decisions to Offer Helth Insurnce to Employees Ctherine McLughlin nd Adm Swinurn, June 2014 Employer-sponsored helth insurnce (ESI) is the dominnt source of coverge for nonelderly dults
More informationDistributions. (corresponding to the cumulative distribution function for the discrete case).
Distributions Recll tht n integrble function f : R [,] such tht R f()d = is clled probbility density function (pdf). The distribution function for the pdf is given by F() = (corresponding to the cumultive
More informationM5A42 APPLIED STOCHASTIC PROCESSES PROBLEM SHEET 1 SOLUTIONS Term 1 2010-2011
M5A42 APPLIED STOCHASTIC PROCESSES PROBLEM SHEET 1 SOLUTIONS Term 1 21-211 1. Clculte the men, vrince nd chrcteristic function of the following probbility density functions. ) The exponentil distribution
More informationGENERALIZED QUATERNIONS SERRET-FRENET AND BISHOP FRAMES SERRET-FRENET VE BISHOP ÇATILARI
Sy 9, Arlk 0 GENERALIZED QUATERNIONS SERRET-FRENET AND BISHOP FRAMES Erhn ATA*, Ysemin KEMER, Ali ATASOY Dumlupnr Uniersity, Fculty of Science nd Arts, Deprtment of Mthemtics, KÜTAHYA, et@dpu.edu.tr ABSTRACT
More informationDecision Rule Extraction from Trained Neural Networks Using Rough Sets
Decision Rule Extrction from Trined Neurl Networks Using Rough Sets Alin Lzr nd Ishwr K. Sethi Vision nd Neurl Networks Lbortory Deprtment of Computer Science Wyne Stte University Detroit, MI 48 ABSTRACT
More informationDerivatives and Rates of Change
Section 2.1 Derivtives nd Rtes of Cnge 2010 Kiryl Tsiscnk Derivtives nd Rtes of Cnge Te Tngent Problem EXAMPLE: Grp te prbol y = x 2 nd te tngent line t te point P(1,1). Solution: We ve: DEFINITION: Te
More information19. The Fermat-Euler Prime Number Theorem
19. The Fermt-Euler Prime Number Theorem Every prime number of the form 4n 1 cn be written s sum of two squres in only one wy (side from the order of the summnds). This fmous theorem ws discovered bout
More informationUnderstanding Basic Analog Ideal Op Amps
Appliction Report SLAA068A - April 2000 Understnding Bsic Anlog Idel Op Amps Ron Mncini Mixed Signl Products ABSTRACT This ppliction report develops the equtions for the idel opertionl mplifier (op mp).
More informationNovel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm
Bibhudendr chry, Girij Snkr Rth, Srt Kumr Ptr, nd Sroj Kumr Pnigrhy Novel Methods of Generting Self-Invertible Mtrix for Hill Cipher lgorithm Bibhudendr chry Deprtment of Electronics & Communiction Engineering
More information. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2
7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6
More informationFactoring RSA moduli with weak prime factors
Fctoring RSA moduli with we prime fctors Abderrhmne Nitj 1 nd Tjjeeddine Rchidi 2 1 Lbortoire de Mthémtiques Nicols Oresme Université de Cen Bsse Normndie, Frnce bderrhmne.nitj@unicen.fr 2 School of Science
More informationLecture 25: More Rectangular Domains: Neumann Problems, mixed BC, and semi-infinite strip problems
Introductory lecture notes on Prtil ifferentil Equtions - y Anthony Peirce UBC 1 Lecture 5: More Rectngulr omins: Neumnn Prolems, mixed BC, nd semi-infinite strip prolems Compiled 6 Novemer 13 In this
More informationExam 1 Study Guide. Differentiation and Anti-differentiation Rules from Calculus I
Exm Stuy Guie Mth 2020 - Clculus II, Winter 204 The following is list of importnt concepts from ech section tht will be teste on exm. This is not complete list of the mteril tht you shoul know for the
More information