Applied Linear Algebra

Size: px
Start display at page:

Download "Applied Linear Algebra"

Transcription

1 Applied Linear Algebra by Peter J. Olver and Chehrzad Shakiban Corrections to Instructor s Solution Manual..4d A =, x = u v, b = ; 0 w e A = 5, 5 f b =..4.5a Last updated: December 5, i a b and b 0; ii a = b 0, or a =, b = 0; iii a, b = 0..8.e 0,0,0 T ;..8a By induction, we can show that, for n and x > 0, f n x = Q n x x n where Q n x is a polynomial of degree n. Thus, Q lim x 0 fn x = lim n x + x 0 + x n e /x e /x, = Q n 0 lim y yn e y = 0 = lim x 0 fn x, because the exponential e y goes to zero faster than any power of y goes to..5.5b x =,,0 T, z = z 7, 7, T ;.5.d... while cokeru has basis 0,0,0, T. /5/ c 0 Peter J. Olver

2 .5.b Yes, the preceding example can put into row echelon form by the following elementary row operations of type #: 0 0 R R +R 0 R R R Indeed, Exercise.4.8 shows how to interchange any two rows, modulo multiplying one by an inessential minus sign, using only elementary row operations of type #. As a consequence, one can reduce any matrix to row echelon form without any row interchanges! The answer in the manual implicitly assumes that the row operations had to be done in the standard order. But this is not stated in the exercise as written..5.4 True. If kera = kerb R n, then both matrices have n columns, and so n ranka = dimkera = dimkerb = n rankb...6b... plane has length.....0c If v is any element of V, then we can write v = c v + +c n v n as a linear combination of the basis elements, and so, by bilinearity, x y,v = c x y,v + +c n x y,v n = c x,v y,v + +c n x,vn y,v n = 0. Since this holds for all v V, the result in part a implies x = y...b Missing square on v,w in formula: sin θ = cos θ = v w v,w v w = v w v w..4.ii andv Change null vectors to null directions..4.a L = A T T A T is....5.b 0 = Change all w s to v s. 4..4c When b, the minimum is Delete c. Just the label, not the formula coming afterwards a Change the interpolating polynomial to an interpolating polynomial. /5/ c 0 Peter J. Olver

3 4.4.5 ThesolutiongiveninthemanualisforthesquareS = { 0 x, 0 y }. When S = { x, y }, use the following: Solution:a z =, b z = x y, c z = One way to solve this is by direct computation. A more sophisticated approach is to apply the Cholesky factorization.70 to the inner product matrix: K = MM T. Then, v,w = v T Kw = v T ŵ where v = M T v, ŵ = M T w. Therefore, v,v form an orthonormal basis relative to v,w = v T Kw if and only if v = M T v, v = M T v, form an orthonormal basis for the dot product, and hence of the form determined in 0 Exercise 5... Using this we find: a M = 0 sinθ ±, for any 0 θ < π. b M = cosθ cosθ sinθ v = ±, for any 0 θ < π. cosθ 0, so v =, so v = cosθ sinθ p 0 x =, p x = x, p x = x, p 4 x = x 9 0 x. The solution given is for the interval [0,], not [,] iic 5.5.6iid , , v = cosθ+sinθ sinθ 5.6.0c The solution corresponds to the revised exercise for the system x +x +x = b, x +x = b, x +5x +7x = b, x +x +4x = b 4. For the given system, the cokernel basis is,,,0 T, and the compatibility condition is b +b +b = 0., /5/ c 0 Peter J. Olver

4 5.7.a,b,c To avoid any confusion, delete the superfluous last sample value in the first equation: a i f 0 =, f =, f =. ii e ix +e ix = cosx; b i f 0 =, f = 5, f = + 5, f = + 5, f 4 = 5; ii e ix e ix + e ix +e ix = cosx+cosx; c i f 0 = 6, f = +e πi/5 +e 4πi/5 = +.765i, f = +e πi/5 +e 4πi/5 = i, f = +e πi/5 +e 4πi/5 =.0777i, f 4 = +e πi/5 +e 4πi/5 =.765i; ii e ix ++e ix = +cosx+i sinx+cosx i sinx; d i f 0 = f = f = f 4 = f 5 = 0, f = 6; ii e ix +e ix e ix +e 4ix e 5ix = cosx+cosx cosx+cos4x cos5x+i sinx+sinx sinx+sin4x sin5x. 6..b The solution given in the manual corresponds to the revised exercise with incidence matrix Forthegivenmatrix,thesolutionis b u v u = f, u + v = g, u + u + v = f, u + v = g. 7.4.iib vt = c e t +c e t/ Set d = c in the written solution d Note: The solution is correct provided, for L:V V, one uses the same inner product on the domain and target copies of V. If different inner products are used, then the identity map is not self-adjoint, I I, and so, in this more general situation, L L. 8..a Interchange solutionsb andc., /5/ 4 c 0 Peter J. Olver

5 9.4.8 Change e t:a to e ta The solution given in the manual is for b =,,7 T. When b = 4,0,4 T, use the following: Solution: a x = = b x = 0, x = 0 4 c x k+ = d x = ; , x =, x = , with error e =.7500 x k + 0 ; , x = ; ; the error at the third iteration is e = ; the Gauss-Seidel approximation is more accurate e x k+ = 0 x k + ; f ρt J = 4 =.40, g ρt GS = =.8075, so Gauss Seidel converges about logρ GS /logρ J =.046 times as fast. h Approximately log /logρ GS 8.5 iterations. i Under Gauss Seidel, x 9 = , with error e 9 = Changeupperintegrationlimitintheformulafora = π y fzdz dy. π 0 0 b..f ϕx = δx 5 δx ; ϕxuxdx = u u for 5 a < < < b. a /5/ 5 c 0 Peter J. Olver

6 {, x >,..8d f x = 4δx++4δx +, x <, = 4δx++4δx + σx++σx, f x = 4δ x++4δ x δx++δx...a The symbol on the vertical axis should be n, not n...5 Replace σ y x by σ y x...7 In displayed equation, delete extra parenthesis at end of δ k ξ x twice; replace u by u in penultimate term: δ k ξ,u...9 Delete one repetition of On the other hand... a x y, 0 x y n, u n x = 4 nx + n xy 4 ny + y + x 4n, x y n, y x, y + n x. b Since u n x = Gx,y for all x y, we have lim n u n n x = Gx,y for all x y, while lim u n n y = lim y y n 4n = y y = Gy,y. Or one can appeal to continuity to infer this. This limit reflects the fact that the external forces converge to the delta function: lim f n n x = δx y. 0. c End of first line in final equation: I x + I z dα dx + I w dβ dx /5/ 6 c 0 Peter J. Olver

7 ..ci u x = x 5 +x, ii P[u] = iii P[u ] = 7 0 =.85, [ x u +x u ] dx, u = u = 0, iv P[x x] = 6 =.8, P[ sin πx] = div P [ 4 x+x+] = , P [ 0 xx+x+] = c Unique minimizer: u x = x+ +sinxcos log sincosx. The given solution is for the boundary conditions u = u = 0... ux = x 9 + logx 9 log.5. Change sign of last expression: = ω + e ω/ e ωx +e ω e ωx. ω +e ω/ sinhωy sinhωx, x < y,.5.7b For λ = ω ωsinhω < 0, Gx,y = sinhωx sinhωy, x > y; { ωsinhω xy, x < y, for λ = 0, Gx,y = yx, x > y; sinωy sinωx, x < y, for λ = ω n π ωsinω > 0, Gx,y = sinωx sinωy, x > y. ωsinω.5.9c i,ii,iii Replace b a by. Acknowledgments: We would particularly like to thank to David Hiebeler, University of Maine, for alerting us to many of these corrections. /5/ 7 c 0 Peter J. Olver

Applied Linear Algebra, First Edition

Applied Linear Algebra, First Edition Applied Linear Algebra, First Edition by Peter J. Olver and Chehrzad Shakiban Corrections to First Printing (2006) Page xvii First bullet item The core: Add the following as a footnote: Last updated: July,

More information

Linear Algebra II. 7 Inner product spaces. Notes 7 16th December Inner products and orthonormal bases

Linear Algebra II. 7 Inner product spaces. Notes 7 16th December Inner products and orthonormal bases MTH6140 Linear Algebra II Notes 7 16th December 2010 7 Inner product spaces Ordinary Euclidean space is a 3-dimensional vector space over R, but it is more than that: the extra geometric structure (lengths,

More information

Applied Linear Algebra

Applied Linear Algebra Applied Linear Algebra Peter J. Olver School of Mathematics University of Minnesota Minneapolis, MN 55455 olver@math.umn.edu http://www.math.umn.edu/ olver Chehrzad Shakiban Department of Mathematics University

More information

G1110 & 852G1 Numerical Linear Algebra

G1110 & 852G1 Numerical Linear Algebra The University of Sussex Department of Mathematics G & 85G Numerical Linear Algebra Lecture Notes Autumn Term Kerstin Hesse (w aw S w a w w (w aw H(wa = (w aw + w Figure : Geometric explanation of the

More information

Reduction to the associated homogeneous system via a particular solution

Reduction to the associated homogeneous system via a particular solution June PURDUE UNIVERSITY Study Guide for the Credit Exam in (MA 5) Linear Algebra This study guide describes briefly the course materials to be covered in MA 5. In order to be qualified for the credit, one

More information

Introduction to Partial Differential Equations

Introduction to Partial Differential Equations Introduction to Partial Differential Equations by Peter J Olver Page ix Corrections to First Printing (2014) Last updated: May 2, 2017 Line 7: Change In order the make progress to In order to make progress

More information

Math 1310 Final Exam

Math 1310 Final Exam Math 1310 Final Exam December 11, 2014 NAME: INSTRUCTOR: Write neatly and show all your work in the space provided below each question. You may use the back of the exam pages if you need additional space

More information

Numerical Methods for Engineers, Second edition: Chapter 1 Errata

Numerical Methods for Engineers, Second edition: Chapter 1 Errata Numerical Methods for Engineers, Second edition: Chapter 1 Errata 1. p.2 first line, remove the Free Software Foundation at 2. p.2 sixth line of the first proper paragraph, fe95.res should be replaced

More information

First order differential equations

First order differential equations First order differential equations Samy Tindel Purdue University Differential equations and linear algebra - MA 262 Taken from Differential equations and linear algebra by Goode and Annin Samy T. First

More information

MS 3011 Exercises. December 11, 2013

MS 3011 Exercises. December 11, 2013 MS 3011 Exercises December 11, 2013 The exercises are divided into (A) easy (B) medium and (C) hard. If you are particularly interested I also have some projects at the end which will deepen your understanding

More information

Solved Examples. (Highest power of x in numerator and denominator is ½. Dividing numerator and denominator by x)

Solved Examples. (Highest power of x in numerator and denominator is ½. Dividing numerator and denominator by x) Solved Examples Example 1: (i) (ii) lim x (x 4 + 2x 3 +3) / (2x 4 -x+2) lim x x ( (x+c)- x) (iii) lim n (1-2+3-4+...(2n-1)-2n)/ (n 2 +1) (iv) lim x 0 ((1+x) 5-1)/3x+5x 2 (v) lim x 2 ( (x+7)-3 (2x-3))/((x+6)

More information

Bessel s Equation. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics

Bessel s Equation. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics Bessel s Equation MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Background Bessel s equation of order ν has the form where ν is a constant. x 2 y + xy

More information

Corrections and Minor Revisions of Mathematical Methods in the Physical Sciences, third edition, by Mary L. Boas (deceased)

Corrections and Minor Revisions of Mathematical Methods in the Physical Sciences, third edition, by Mary L. Boas (deceased) Corrections and Minor Revisions of Mathematical Methods in the Physical Sciences, third edition, by Mary L. Boas (deceased) Updated December 6, 2017 by Harold P. Boas This list includes all errors known

More information

Next topics: Solving systems of linear equations

Next topics: Solving systems of linear equations Next topics: Solving systems of linear equations 1 Gaussian elimination (today) 2 Gaussian elimination with partial pivoting (Week 9) 3 The method of LU-decomposition (Week 10) 4 Iterative techniques:

More information

The Gram-Schmidt Process 1

The Gram-Schmidt Process 1 The Gram-Schmidt Process In this section all vector spaces will be subspaces of some R m. Definition.. Let S = {v...v n } R m. The set S is said to be orthogonal if v v j = whenever i j. If in addition

More information

1. General Vector Spaces

1. General Vector Spaces 1.1. Vector space axioms. 1. General Vector Spaces Definition 1.1. Let V be a nonempty set of objects on which the operations of addition and scalar multiplication are defined. By addition we mean a rule

More information

LINEAR ALGEBRA QUESTION BANK

LINEAR ALGEBRA QUESTION BANK LINEAR ALGEBRA QUESTION BANK () ( points total) Circle True or False: TRUE / FALSE: If A is any n n matrix, and I n is the n n identity matrix, then I n A = AI n = A. TRUE / FALSE: If A, B are n n matrices,

More information

Physics 116C The Distribution of the Sum of Random Variables

Physics 116C The Distribution of the Sum of Random Variables Physics 116C The Distribution of the Sum of Random Variables Peter Young (Dated: December 2, 2013) Consider a random variable with a probability distribution P(x). The distribution is normalized, i.e.

More information

Linear algebra II Homework #1 due Thursday, Feb A =

Linear algebra II Homework #1 due Thursday, Feb A = Homework #1 due Thursday, Feb. 1 1. Find the eigenvalues and the eigenvectors of the matrix [ ] 3 2 A =. 1 6 2. Find the eigenvalues and the eigenvectors of the matrix 3 2 2 A = 2 3 2. 2 2 1 3. The following

More information

Summer 2017 MATH Solution to Exercise 5

Summer 2017 MATH Solution to Exercise 5 Summer 07 MATH00 Solution to Exercise 5. Find the partial derivatives of the following functions: (a (xy 5z/( + x, (b x/ x + y, (c arctan y/x, (d log((t + 3 + ts, (e sin(xy z 3, (f x α, x = (x,, x n. (a

More information

Fourier and Partial Differential Equations

Fourier and Partial Differential Equations Chapter 5 Fourier and Partial Differential Equations 5.1 Fourier MATH 294 SPRING 1982 FINAL # 5 5.1.1 Consider the function 2x, 0 x 1. a) Sketch the odd extension of this function on 1 x 1. b) Expand the

More information

Analysis/Calculus Review Day 3

Analysis/Calculus Review Day 3 Analysis/Calculus Review Day 3 Arvind Saibaba arvindks@stanford.edu Institute of Computational and Mathematical Engineering Stanford University September 15, 2010 Big- Oh and Little- Oh Notation We write

More information

HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION)

HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION) HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION) PROFESSOR STEVEN MILLER: BROWN UNIVERSITY: SPRING 2007 1. CHAPTER 1: MATRICES AND GAUSSIAN ELIMINATION Page 9, # 3: Describe

More information

NATIONAL BOARD FOR HIGHER MATHEMATICS. M. A. and M.Sc. Scholarship Test. September 22, Time Allowed: 150 Minutes Maximum Marks: 30

NATIONAL BOARD FOR HIGHER MATHEMATICS. M. A. and M.Sc. Scholarship Test. September 22, Time Allowed: 150 Minutes Maximum Marks: 30 NATIONAL BOARD FOR HIGHER MATHEMATICS M A and MSc Scholarship Test September 22, 2018 Time Allowed: 150 Minutes Maximum Marks: 30 Please read, carefully, the instructions that follow INSTRUCTIONS TO CANDIDATES

More information

Solving Linear Systems Using Gaussian Elimination

Solving Linear Systems Using Gaussian Elimination Solving Linear Systems Using Gaussian Elimination DEFINITION: A linear equation in the variables x 1,..., x n is an equation that can be written in the form a 1 x 1 +...+a n x n = b, where a 1,...,a n

More information

Elementary Linear Algebra

Elementary Linear Algebra Matrices J MUSCAT Elementary Linear Algebra Matrices Definition Dr J Muscat 2002 A matrix is a rectangular array of numbers, arranged in rows and columns a a 2 a 3 a n a 2 a 22 a 23 a 2n A = a m a mn We

More information

Diagnostic quiz for M337 Complex analysis

Diagnostic quiz for M337 Complex analysis Diagnostic quiz for M337 Complex analysis The aim of this diagnostic quiz is to help you assess how well prepared you are for M337, and to identify topics that you should revise or study before beginning

More information

ELEMENTARY LINEAR ALGEBRA

ELEMENTARY LINEAR ALGEBRA ELEMENTARY LINEAR ALGEBRA K. R. MATTHEWS DEPARTMENT OF MATHEMATICS UNIVERSITY OF QUEENSLAND Corrected Version, 7th April 013 Comments to the author at keithmatt@gmail.com Chapter 1 LINEAR EQUATIONS 1.1

More information

j=1 x j p, if 1 p <, x i ξ : x i < ξ} 0 as p.

j=1 x j p, if 1 p <, x i ξ : x i < ξ} 0 as p. LINEAR ALGEBRA Fall 203 The final exam Almost all of the problems solved Exercise Let (V, ) be a normed vector space. Prove x y x y for all x, y V. Everybody knows how to do this! Exercise 2 If V is a

More information

M.SC. PHYSICS - II YEAR

M.SC. PHYSICS - II YEAR MANONMANIAM SUNDARANAR UNIVERSITY DIRECTORATE OF DISTANCE & CONTINUING EDUCATION TIRUNELVELI 627012, TAMIL NADU M.SC. PHYSICS - II YEAR DKP26 - NUMERICAL METHODS (From the academic year 2016-17) Most Student

More information

Problem Set 1. This week. Please read all of Chapter 1 in the Strauss text.

Problem Set 1. This week. Please read all of Chapter 1 in the Strauss text. Math 425, Spring 2015 Jerry L. Kazdan Problem Set 1 Due: Thurs. Jan. 22 in class. [Late papers will be accepted until 1:00 PM Friday.] This is rust remover. It is essentially Homework Set 0 with a few

More information

Linear algebra II Homework #1 solutions A = This means that every eigenvector with eigenvalue λ = 1 must have the form

Linear algebra II Homework #1 solutions A = This means that every eigenvector with eigenvalue λ = 1 must have the form Linear algebra II Homework # solutions. Find the eigenvalues and the eigenvectors of the matrix 4 6 A =. 5 Since tra = 9 and deta = = 8, the characteristic polynomial is f(λ) = λ (tra)λ+deta = λ 9λ+8 =

More information

Solving Systems of Linear Equations Using Matrices

Solving Systems of Linear Equations Using Matrices Solving Systems of Linear Equations Using Matrices What is a Matrix? A matrix is a compact grid or array of numbers. It can be created from a system of equations and used to solve the system of equations.

More information

Linear Maps and Matrices

Linear Maps and Matrices Linear Maps and Matrices Maps Suppose that V and W are sets A map F : V W is a function; that is, to every v V there is assigned a unique element w F v in W Two maps F : V W and G : V W are equal if F

More information

Functional Analysis Exercise Class

Functional Analysis Exercise Class Functional Analysis Exercise Class Week: December 4 8 Deadline to hand in the homework: your exercise class on week January 5. Exercises with solutions ) Let H, K be Hilbert spaces, and A : H K be a linear

More information

1 Distributions (due January 22, 2009)

1 Distributions (due January 22, 2009) Distributions (due January 22, 29). The distribution derivative of the locally integrable function ln( x ) is the principal value distribution /x. We know that, φ = lim φ(x) dx. x ɛ x Show that x, φ =

More information

MATH 205C: STATIONARY PHASE LEMMA

MATH 205C: STATIONARY PHASE LEMMA MATH 205C: STATIONARY PHASE LEMMA For ω, consider an integral of the form I(ω) = e iωf(x) u(x) dx, where u Cc (R n ) complex valued, with support in a compact set K, and f C (R n ) real valued. Thus, I(ω)

More information

Contents. Preface for the Instructor. Preface for the Student. xvii. Acknowledgments. 1 Vector Spaces 1 1.A R n and C n 2

Contents. Preface for the Instructor. Preface for the Student. xvii. Acknowledgments. 1 Vector Spaces 1 1.A R n and C n 2 Contents Preface for the Instructor xi Preface for the Student xv Acknowledgments xvii 1 Vector Spaces 1 1.A R n and C n 2 Complex Numbers 2 Lists 5 F n 6 Digression on Fields 10 Exercises 1.A 11 1.B Definition

More information

Blue Pelican Calculus First Semester

Blue Pelican Calculus First Semester Blue Pelican Calculus First Semester Student Version 1.01 Copyright 2011-2013 by Charles E. Cook; Refugio, Tx Edited by Jacob Cobb (All rights reserved) Calculus AP Syllabus (First Semester) Unit 1: Function

More information

Quaternion Dynamics, Part 1 Functions, Derivatives, and Integrals. Gary D. Simpson. rev 00 Dec 27, 2014.

Quaternion Dynamics, Part 1 Functions, Derivatives, and Integrals. Gary D. Simpson. rev 00 Dec 27, 2014. Quaternion Dynamics, Part 1 Functions, Derivatives, and Integrals Gary D. Simpson gsim100887@aol.com rev 00 Dec 27, 2014 Summary Definitions are presented for "quaternion functions" of a quaternion. Polynomial

More information

Degree Master of Science in Mathematical Modelling and Scientific Computing Mathematical Methods I Thursday, 12th January 2012, 9:30 a.m.- 11:30 a.m.

Degree Master of Science in Mathematical Modelling and Scientific Computing Mathematical Methods I Thursday, 12th January 2012, 9:30 a.m.- 11:30 a.m. Degree Master of Science in Mathematical Modelling and Scientific Computing Mathematical Methods I Thursday, 12th January 2012, 9:30 a.m.- 11:30 a.m. Candidates should submit answers to a maximum of four

More information

Problem Max. Possible Points Total

Problem Max. Possible Points Total MA 262 Exam 1 Fall 2011 Instructor: Raphael Hora Name: Max Possible Student ID#: 1234567890 1. No books or notes are allowed. 2. You CAN NOT USE calculators or any electronic devices. 3. Show all work

More information

2. Second-order Linear Ordinary Differential Equations

2. Second-order Linear Ordinary Differential Equations Advanced Engineering Mathematics 2. Second-order Linear ODEs 1 2. Second-order Linear Ordinary Differential Equations 2.1 Homogeneous linear ODEs 2.2 Homogeneous linear ODEs with constant coefficients

More information

Chapter 2 Subspaces of R n and Their Dimensions

Chapter 2 Subspaces of R n and Their Dimensions Chapter 2 Subspaces of R n and Their Dimensions Vector Space R n. R n Definition.. The vector space R n is a set of all n-tuples (called vectors) x x 2 x =., where x, x 2,, x n are real numbers, together

More information

MAT Linear Algebra Collection of sample exams

MAT Linear Algebra Collection of sample exams MAT 342 - Linear Algebra Collection of sample exams A-x. (0 pts Give the precise definition of the row echelon form. 2. ( 0 pts After performing row reductions on the augmented matrix for a certain system

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) A.J.Hobson JUST THE MATHS UNIT NUMBER.5 DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) by A.J.Hobson.5. Maclaurin s series.5. Standard series.5.3 Taylor s series.5.4 Exercises.5.5 Answers to exercises

More information

Some definitions. Math 1080: Numerical Linear Algebra Chapter 5, Solving Ax = b by Optimization. A-inner product. Important facts

Some definitions. Math 1080: Numerical Linear Algebra Chapter 5, Solving Ax = b by Optimization. A-inner product. Important facts Some definitions Math 1080: Numerical Linear Algebra Chapter 5, Solving Ax = b by Optimization M. M. Sussman sussmanm@math.pitt.edu Office Hours: MW 1:45PM-2:45PM, Thack 622 A matrix A is SPD (Symmetric

More information

MATH 2554 (Calculus I)

MATH 2554 (Calculus I) MATH 2554 (Calculus I) Dr. Ashley K. University of Arkansas February 21, 2015 Table of Contents Week 6 1 Week 6: 16-20 February 3.5 Derivatives as Rates of Change 3.6 The Chain Rule 3.7 Implicit Differentiation

More information

Solution to Review Problems for Midterm II

Solution to Review Problems for Midterm II Solution to Review Problems for Midterm II Midterm II: Monday, October 18 in class Topics: 31-3 (except 34) 1 Use te definition of derivative f f(x+) f(x) (x) lim 0 to find te derivative of te functions

More information

EXERCISES ON DETERMINANTS, EIGENVALUES AND EIGENVECTORS. 1. Determinants

EXERCISES ON DETERMINANTS, EIGENVALUES AND EIGENVECTORS. 1. Determinants EXERCISES ON DETERMINANTS, EIGENVALUES AND EIGENVECTORS. Determinants Ex... Let A = 0 4 4 2 0 and B = 0 3 0. (a) Compute 0 0 0 0 A. (b) Compute det(2a 2 B), det(4a + B), det(2(a 3 B 2 )). 0 t Ex..2. For

More information

ELEMENTARY LINEAR ALGEBRA

ELEMENTARY LINEAR ALGEBRA ELEMENTARY LINEAR ALGEBRA K. R. MATTHEWS DEPARTMENT OF MATHEMATICS UNIVERSITY OF QUEENSLAND Second Online Version, December 1998 Comments to the author at krm@maths.uq.edu.au Contents 1 LINEAR EQUATIONS

More information

Lecture 2 Systems of Linear Equations and Matrices, Continued

Lecture 2 Systems of Linear Equations and Matrices, Continued Lecture 2 Systems of Linear Equations and Matrices, Continued Math 19620 Outline of Lecture Algorithm for putting a matrix in row reduced echelon form - i.e. Gauss-Jordan Elimination Number of Solutions

More information

ECONOMICS 207 SPRING 2006 LABORATORY EXERCISE 5 KEY. 8 = 10(5x 2) = 9(3x + 8), x 50x 20 = 27x x = 92 x = 4. 8x 2 22x + 15 = 0 (2x 3)(4x 5) = 0

ECONOMICS 207 SPRING 2006 LABORATORY EXERCISE 5 KEY. 8 = 10(5x 2) = 9(3x + 8), x 50x 20 = 27x x = 92 x = 4. 8x 2 22x + 15 = 0 (2x 3)(4x 5) = 0 ECONOMICS 07 SPRING 006 LABORATORY EXERCISE 5 KEY Problem. Solve the following equations for x. a 5x 3x + 8 = 9 0 5x 3x + 8 9 8 = 0(5x ) = 9(3x + 8), x 0 3 50x 0 = 7x + 7 3x = 9 x = 4 b 8x x + 5 = 0 8x

More information

Lecture 23: 6.1 Inner Products

Lecture 23: 6.1 Inner Products Lecture 23: 6.1 Inner Products Wei-Ta Chu 2008/12/17 Definition An inner product on a real vector space V is a function that associates a real number u, vwith each pair of vectors u and v in V in such

More information

Ph.D. Katarína Bellová Page 1 Mathematics 2 (10-PHY-BIPMA2) EXAM - Solutions, 20 July 2017, 10:00 12:00 All answers to be justified.

Ph.D. Katarína Bellová Page 1 Mathematics 2 (10-PHY-BIPMA2) EXAM - Solutions, 20 July 2017, 10:00 12:00 All answers to be justified. PhD Katarína Bellová Page 1 Mathematics 2 (10-PHY-BIPMA2 EXAM - Solutions, 20 July 2017, 10:00 12:00 All answers to be justified Problem 1 [ points]: For which parameters λ R does the following system

More information

MATH 425, FINAL EXAM SOLUTIONS

MATH 425, FINAL EXAM SOLUTIONS MATH 425, FINAL EXAM SOLUTIONS Each exercise is worth 50 points. Exercise. a The operator L is defined on smooth functions of (x, y by: Is the operator L linear? Prove your answer. L (u := arctan(xy u

More information

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8 1 To solve the system x 1 + x 2 = 4 2x 1 9x 2 = 2 we find an (easier to solve) equivalent system as follows: Replace equation 2 with (2 times equation 1 + equation 2): x 1 + x 2 = 4 Solve equation 2 for

More information

Homework 2 Foundations of Computational Math 2 Spring 2019

Homework 2 Foundations of Computational Math 2 Spring 2019 Homework 2 Foundations of Computational Math 2 Spring 2019 Problem 2.1 (2.1.a) Suppose (v 1,λ 1 )and(v 2,λ 2 ) are eigenpairs for a matrix A C n n. Show that if λ 1 λ 2 then v 1 and v 2 are linearly independent.

More information

Span and Linear Independence

Span and Linear Independence Span and Linear Independence It is common to confuse span and linear independence, because although they are different concepts, they are related. To see their relationship, let s revisit the previous

More information

The Four Fundamental Subspaces

The Four Fundamental Subspaces The Four Fundamental Subspaces Introduction Each m n matrix has, associated with it, four subspaces, two in R m and two in R n To understand their relationships is one of the most basic questions in linear

More information

MSc Mas6002, Introductory Material Mathematical Methods Exercises

MSc Mas6002, Introductory Material Mathematical Methods Exercises MSc Mas62, Introductory Material Mathematical Methods Exercises These exercises are on a range of mathematical methods which are useful in different parts of the MSc, especially calculus and linear algebra.

More information

Note: Final Exam is at 10:45 on Tuesday, 5/3/11 (This is the Final Exam time reserved for our labs). From Practice Test I

Note: Final Exam is at 10:45 on Tuesday, 5/3/11 (This is the Final Exam time reserved for our labs). From Practice Test I MA Practice Final Answers in Red 4/8/ and 4/9/ Name Note: Final Exam is at :45 on Tuesday, 5// (This is the Final Exam time reserved for our labs). From Practice Test I Consider the integral 5 x dx. Sketch

More information

Review of matrices. Let m, n IN. A rectangle of numbers written like A =

Review of matrices. Let m, n IN. A rectangle of numbers written like A = Review of matrices Let m, n IN. A rectangle of numbers written like a 11 a 12... a 1n a 21 a 22... a 2n A =...... a m1 a m2... a mn where each a ij IR is called a matrix with m rows and n columns or an

More information

Chapter 4: Partial differentiation

Chapter 4: Partial differentiation Chapter 4: Partial differentiation It is generally the case that derivatives are introduced in terms of functions of a single variable. For example, y = f (x), then dy dx = df dx = f. However, most of

More information

OR MSc Maths Revision Course

OR MSc Maths Revision Course OR MSc Maths Revision Course Tom Byrne School of Mathematics University of Edinburgh t.m.byrne@sms.ed.ac.uk 15 September 2017 General Information Today JCMB Lecture Theatre A, 09:30-12:30 Mathematics revision

More information

Quadratic reciprocity (after Weil) 1. Standard set-up and Poisson summation

Quadratic reciprocity (after Weil) 1. Standard set-up and Poisson summation (September 17, 010) Quadratic reciprocity (after Weil) Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ I show that over global fields (characteristic not ) the quadratic norm residue

More information

This practice exam is intended to help you prepare for the final exam for MTH 142 Calculus II.

This practice exam is intended to help you prepare for the final exam for MTH 142 Calculus II. MTH 142 Practice Exam Chapters 9-11 Calculus II With Analytic Geometry Fall 2011 - University of Rhode Island This practice exam is intended to help you prepare for the final exam for MTH 142 Calculus

More information

MATH 240 Spring, Chapter 1: Linear Equations and Matrices

MATH 240 Spring, Chapter 1: Linear Equations and Matrices MATH 240 Spring, 2006 Chapter Summaries for Kolman / Hill, Elementary Linear Algebra, 8th Ed. Sections 1.1 1.6, 2.1 2.2, 3.2 3.8, 4.3 4.5, 5.1 5.3, 5.5, 6.1 6.5, 7.1 7.2, 7.4 DEFINITIONS Chapter 1: Linear

More information

MATH 31BH Homework 5 Solutions

MATH 31BH Homework 5 Solutions MATH 3BH Homework 5 Solutions February 4, 204 Problem.8.2 (a) Let x t f y = x 2 + y 2 + 2z 2 and g(t) = t 2. z t 3 Then by the chain rule a a a D(g f) b = Dg f b Df b c c c = [Dg(a 2 + b 2 + 2c 2 )] [

More information

MATH 369 Linear Algebra

MATH 369 Linear Algebra Assignment # Problem # A father and his two sons are together 00 years old. The father is twice as old as his older son and 30 years older than his younger son. How old is each person? Problem # 2 Determine

More information

Page Problem Score Max Score a 8 12b a b 10 14c 6 6

Page Problem Score Max Score a 8 12b a b 10 14c 6 6 Fall 14 MTH 34 FINAL EXAM December 8, 14 Name: PID: Section: Instructor: DO NOT WRITE BELOW THIS LINE. Go to the next page. Page Problem Score Max Score 1 5 5 1 3 5 4 5 5 5 6 5 7 5 8 5 9 5 1 5 11 1 3 1a

More information

Chapter 2: Differentiation

Chapter 2: Differentiation Chapter 2: Differentiation Spring 2018 Department of Mathematics Hong Kong Baptist University 1 / 82 2.1 Tangent Lines and Their Slopes This section deals with the problem of finding a straight line L

More information

CSL361 Problem set 4: Basic linear algebra

CSL361 Problem set 4: Basic linear algebra CSL361 Problem set 4: Basic linear algebra February 21, 2017 [Note:] If the numerical matrix computations turn out to be tedious, you may use the function rref in Matlab. 1 Row-reduced echelon matrices

More information

1 Boas, problem p.564,

1 Boas, problem p.564, Physics 6C Solutions to Homewor Set # Fall 0 Boas, problem p.564,.- Solve the following differential equations by series and by another elementary method and chec that the results agree: xy = xy +y ()

More information

MTH Linear Algebra. Study Guide. Dr. Tony Yee Department of Mathematics and Information Technology The Hong Kong Institute of Education

MTH Linear Algebra. Study Guide. Dr. Tony Yee Department of Mathematics and Information Technology The Hong Kong Institute of Education MTH 3 Linear Algebra Study Guide Dr. Tony Yee Department of Mathematics and Information Technology The Hong Kong Institute of Education June 3, ii Contents Table of Contents iii Matrix Algebra. Real Life

More information

A matrix over a field F is a rectangular array of elements from F. The symbol

A matrix over a field F is a rectangular array of elements from F. The symbol Chapter MATRICES Matrix arithmetic A matrix over a field F is a rectangular array of elements from F The symbol M m n (F ) denotes the collection of all m n matrices over F Matrices will usually be denoted

More information

CLASSIFICATION AND PRINCIPLE OF SUPERPOSITION FOR SECOND ORDER LINEAR PDE

CLASSIFICATION AND PRINCIPLE OF SUPERPOSITION FOR SECOND ORDER LINEAR PDE CLASSIFICATION AND PRINCIPLE OF SUPERPOSITION FOR SECOND ORDER LINEAR PDE 1. Linear Partial Differential Equations A partial differential equation (PDE) is an equation, for an unknown function u, that

More information

Linear Algebra Notes. Lecture Notes, University of Toronto, Fall 2016

Linear Algebra Notes. Lecture Notes, University of Toronto, Fall 2016 Linear Algebra Notes Lecture Notes, University of Toronto, Fall 2016 (Ctd ) 11 Isomorphisms 1 Linear maps Definition 11 An invertible linear map T : V W is called a linear isomorphism from V to W Etymology:

More information

MTH4101 CALCULUS II REVISION NOTES. 1. COMPLEX NUMBERS (Thomas Appendix 7 + lecture notes) ax 2 + bx + c = 0. x = b ± b 2 4ac 2a. i = 1.

MTH4101 CALCULUS II REVISION NOTES. 1. COMPLEX NUMBERS (Thomas Appendix 7 + lecture notes) ax 2 + bx + c = 0. x = b ± b 2 4ac 2a. i = 1. MTH4101 CALCULUS II REVISION NOTES 1. COMPLEX NUMBERS (Thomas Appendix 7 + lecture notes) 1.1 Introduction Types of numbers (natural, integers, rationals, reals) The need to solve quadratic equations:

More information

MATH 167: APPLIED LINEAR ALGEBRA Chapter 2

MATH 167: APPLIED LINEAR ALGEBRA Chapter 2 MATH 167: APPLIED LINEAR ALGEBRA Chapter 2 Jesús De Loera, UC Davis February 1, 2012 General Linear Systems of Equations (2.2). Given a system of m equations and n unknowns. Now m n is OK! Apply elementary

More information

Inductive and Recursive Moving Frames for Lie Pseudo-Groups

Inductive and Recursive Moving Frames for Lie Pseudo-Groups Inductive and Recursive Moving Frames for Lie Pseudo-Groups Francis Valiquette (Joint work with Peter) Symmetries of Differential Equations: Frames, Invariants and Applications Department of Mathematics

More information

Sum-to-Product and Product-to-Sum Formulas

Sum-to-Product and Product-to-Sum Formulas Sum-to-Product and Product-to-Sum Formulas By: OpenStaxCollege The UCLA marching band (credit: Eric Chan, Flickr). A band marches down the field creating an amazing sound that bolsters the crowd. That

More information

LOWELL JOURNAL. MUST APOLOGIZE. such communication with the shore as Is m i Boimhle, noewwary and proper for the comfort

LOWELL JOURNAL. MUST APOLOGIZE. such communication with the shore as Is m i Boimhle, noewwary and proper for the comfort - 7 7 Z 8 q ) V x - X > q - < Y Y X V - z - - - - V - V - q \ - q q < -- V - - - x - - V q > x - x q - x q - x - - - 7 -» - - - - 6 q x - > - - x - - - x- - - q q - V - x - - ( Y q Y7 - >»> - x Y - ] [

More information

Section 5.8. Taylor Series

Section 5.8. Taylor Series Difference Equations to Differential Equations Section 5.8 Taylor Series In this section we will put together much of the work of Sections 5.-5.7 in the context of a discussion of Taylor series. We begin

More information

Calculus Volume 1 Release Notes 2018

Calculus Volume 1 Release Notes 2018 Calculus Volume 1 Release Notes 2018 Publish Date: March 16, 2018 Revision Number: C1-2016-003(03/18)-MJ Page Count Difference: In the latest edition of Calculus Volume 1, there are 873 pages compared

More information

Section A brief on transformations

Section A brief on transformations Section 127 A brief on transformations consider the transformation another name for it: change of variable x = rcosθ The determinant y = rsinθ r y r is called the Jacobian determinant of x,y with respect

More information

ELEMENTARY LINEAR ALGEBRA

ELEMENTARY LINEAR ALGEBRA ELEMENTARY LINEAR ALGEBRA K R MATTHEWS DEPARTMENT OF MATHEMATICS UNIVERSITY OF QUEENSLAND First Printing, 99 Chapter LINEAR EQUATIONS Introduction to linear equations A linear equation in n unknowns x,

More information

Scientific Computing

Scientific Computing 2301678 Scientific Computing Chapter 2 Interpolation and Approximation Paisan Nakmahachalasint Paisan.N@chula.ac.th Chapter 2 Interpolation and Approximation p. 1/66 Contents 1. Polynomial interpolation

More information

CALCULUS. Berkant Ustaoğlu CRYPTOLOUNGE.NET

CALCULUS. Berkant Ustaoğlu CRYPTOLOUNGE.NET CALCULUS Berkant Ustaoğlu CRYPTOLOUNGE.NET Secant 1 Definition Let f be defined over an interval I containing u. If x u and x I then f (x) f (u) Q = x u is the difference quotient. Also if h 0, such that

More information

7.2. Matrix Multiplication. Introduction. Prerequisites. Learning Outcomes

7.2. Matrix Multiplication. Introduction. Prerequisites. Learning Outcomes Matrix Multiplication 7.2 Introduction When we wish to multiply matrices together we have to ensure that the operation is possible - and this is not always so. Also, unlike number arithmetic and algebra,

More information

MATH 4030 Differential Geometry Lecture Notes Part 4 last revised on December 4, Elementary tensor calculus

MATH 4030 Differential Geometry Lecture Notes Part 4 last revised on December 4, Elementary tensor calculus MATH 4030 Differential Geometry Lecture Notes Part 4 last revised on December 4, 205 Elementary tensor calculus We will study in this section some basic multilinear algebra and operations on tensors. Let

More information

13 Implicit Differentiation

13 Implicit Differentiation - 13 Implicit Differentiation This sections highlights the difference between explicit and implicit expressions, and focuses on the differentiation of the latter, which can be a very useful tool in mathematics.

More information

Numerical methods. Examples with solution

Numerical methods. Examples with solution Numerical methods Examples with solution CONTENTS Contents. Nonlinear Equations 3 The bisection method............................ 4 Newton s method.............................. 8. Linear Systems LU-factorization..............................

More information

Math review. Math review

Math review. Math review Math review 1 Math review 3 1 series approximations 3 Taylor s Theorem 3 Binomial approximation 3 sin(x), for x in radians and x close to zero 4 cos(x), for x in radians and x close to zero 5 2 some geometry

More information

Math 12 Final Exam Review 1

Math 12 Final Exam Review 1 Math 12 Final Exam Review 1 Part One Calculators are NOT PERMITTED for this part of the exam. 1. a) The sine of angle θ is 1 What are the 2 possible values of θ in the domain 0 θ 2π? 2 b) Draw these angles

More information

UNIT-IV DIFFERENTIATION

UNIT-IV DIFFERENTIATION UNIT-IV DIFFERENTIATION BASIC CONCEPTS OF DIFFERTIATION Consider a function yf(x) of a variable x. Suppose x changes from an initial value x 0 to a final value x 1. Then the increment in x defined to be

More information

Chapter 4: Interpolation and Approximation. October 28, 2005

Chapter 4: Interpolation and Approximation. October 28, 2005 Chapter 4: Interpolation and Approximation October 28, 2005 Outline 1 2.4 Linear Interpolation 2 4.1 Lagrange Interpolation 3 4.2 Newton Interpolation and Divided Differences 4 4.3 Interpolation Error

More information

1 Solving equations 1.1 Kick off with CAS 1. Polynomials 1. Trigonometric symmetry properties 1.4 Trigonometric equations and general solutions 1.5 Literal and simultaneous equations 1.6 Review 1.1 Kick

More information

LINEAR ALGEBRA SUMMARY SHEET.

LINEAR ALGEBRA SUMMARY SHEET. LINEAR ALGEBRA SUMMARY SHEET RADON ROSBOROUGH https://intuitiveexplanationscom/linear-algebra-summary-sheet/ This document is a concise collection of many of the important theorems of linear algebra, organized

More information

Tangent Planes, Linear Approximations and Differentiability

Tangent Planes, Linear Approximations and Differentiability Jim Lambers MAT 80 Spring Semester 009-10 Lecture 5 Notes These notes correspond to Section 114 in Stewart and Section 3 in Marsden and Tromba Tangent Planes, Linear Approximations and Differentiability

More information