HW3 - Due 02/06. Each answer must be mathematically justified. Don t forget your name. 1 2, A = 2 2
|
|
- Delilah Bell
- 5 years ago
- Views:
Transcription
1 HW3 - Due 02/06 Each answer must be mathematically justified Don t forget your name Problem 1 Find a 2 2 matrix B such that B 3 = A, where A = 2 2 If A was diagonal, it would be easy: we would just take the cubic roots of the diagonal elements But A is not diagonal However A is diagonalizable because it is symmetric, so let us first diagonalize A The eigenvalues solve (1 λ)( 2 λ) 4 = λ 2 + λ 6 = (λ 2)(λ + 3) Thus 2 and 3 are eigenvalues We now find eigenvectors: [ 2 2Id = is eigenvector; ] Id = is eigenvector We deduce that A = P DP 1, P = 2 0, D = 0 3 P 1 = Now we set E the diagonal matrix whose elements are the cubic roots of the elements of D; and we define [ 3 ] 2 0 B = P EP 1, E = Then B 3 = P EP 1 P EP 1 P EP 1 = P E 3 P 1 = P DP 1 = A Therefore B responds to the problem Problem 2 Is there a 3 3 symmetric matrix A with distinct eigenvalues and eigenvectors, 3 4 5, 6 7 8? 9 Symmetric matrices admit an orthogonal basis of eigenvectors Because here these eigenvalues are distinct, such a matrix can exist if and only if the above vectors are orthogonal But = = Therefore there are no such matrices 1
2 2 Problem 3 Test whether these quadratic forms are positive definite or negative definite: (a) q 1 (x 1, x 2, x 3 ) = 10x x x x 1 x 2 + 2x 2 x 3 + 2x 3 x 1, (b) q 2 (x 1, x 2, x 3 ) = x x 2 2 4x x 1 x 2 2x 2 x 3 + 4x 1 x 3 (a) q 1 is represented by the symmetric matrix Q 3 = We use the minors test: 10 > 0, > 0 and = > Thus q 1 is definite positive (b) q 2 is represented by the symmetric matrix Q 2 = We use the minors test: 1 > 0, 1 2 = 1 > 0 and = = = 17 Thus q 2 is indefinite Problem 4 Write the quadratic form q(x 1, x 2, x 3 ) = x x x x 1 x 2 + 2x 1 x 3 + 6x 2 x 3 as a sum of squares Deduce that q is positive definite We use the algorithm seen in class: q(x 1, x 2, x 3 ) = (x 1 + x 2 + x 3 ) 2 + x x x 2 x 3 = (x 1 + x 2 + x 3 ) 2 + (x 2 + 2x 3 ) 2 + x 2 3 It is clear that q is positive semidefinite it is a sum of squares To check that it is definite positive, we must observe that these squares do not vanish simultaneously unless x 1 = x 2 = x 3 = 0 If that happens, then x 1 + x 2 + x 3 = 0 x 2 + 2x 3 = 0 x 3 = 0 This is a triangular system and (0, 0, 0) is the unique solution Hence q is definite positive
3 Problem 5 Find the equation of the tangent plane of the graphs of the function (a) f(x, y) = y 3 2y+x at (x, y) = (1, 1); (b) g(x, y, z) = xz+2y 2 z 2 at (x, y, z) = ( 1, 1, 0) (a) We start by computing x f(1, 1) and y f(1, 1): x f(x, y) = 1, x f(1, 1) = 1, y f(x, y) = 3y 2 2, y f(1, 1) = 1, f(1, 1) = 0 Therefore the tangent plane at (1, 1) has equation x 2 + y = z (b) The same strategy yields x g(x, y, z) = z, x g( 1, 1, 0) = 0, y g(x, y, z) = 4yz 2, y g( 1, 1, 0) = 0, z g(x, y, z) = x + 4y 2 z, z g( 1, 1, 0) = 1 In addition, g( 1, 1, 0) = 0 thus the equation of the tangent plane at ( 1, 1, 0) is t = z Problem 6 Find all local minimum and maximum of the following functions: (a) f(x, y) = x 2 + 2x + 2y + 2y 2 + 2xy + 1; (b) g(x, y) = 4x 2 + 4xy + 2y 2 3; (c) h(x, y) = 3x + 3xy + y 3 (a) We compute the directional derivatives: x f(x, y) = 2x y = 2(1 + x + y), p y f = 2 + 4y + 2x = 2(1 + 2y + x) We now look for critical points: we have to solve the system { { { 1 + x + y = x + y = 0 x = y + x = 0 y = 0 y = 0 We now compute the Hessian of f at ( 1, 0): 2 1 f (x, y) = We observe that the Hessian is definite positive: 2 > 0 and > 0 Therefore ( 1, 0) corresponds to a local minimum (b) We compute the directional derivatives: x g(x, y) = 8x + 4y = 4(2x + y), p y g = 4y + 4x = 4(x + y) We now look for critical points: we have to solve the system { { 2x + y = 0 x = 0 x + y = 0 y = 0 We now compute the Hessian of g at (0, 0): g (x, y) =
4 4 We observe that the Hessian is definite positive: 8 > 0 and > 0 Therefore (0, 0) corresponds to a local minimum (c) We first compute the derivatives and the Hessian: 0 3 x h(x, y) = 3 + 3y, y h(x, y) = 3x + 3y 2, h (x, y) = 3 6y The derivatives vanish simultaneously at ( 1, 1) The Hessian at this points is: 0 3 h ( 1, 1) = 3 6 It is indefinite because its determinant is 9 < 0 Thus h has a saddle points at ( 1, 1) and no local minimum or maximum Problem 7 Let f(x, y) = x 2 + 2xy + y 3 + x 3 (a) Show that f has a saddle point at (0, 0) (b) Find some numbers a and b such that the function g(t) = f(at, bt) has a local minimum at t = 0 (c) Find some numbers c and d such that the function h(t) = f(ct, dt) has a local maximum at t = 0 (a) We compute the first derivatives and the Hessian of f: 2 + 6x 2 x f(x, y) = 2x + 2y + 3x 2, y f(x, y) = 2x + 3y 2, f (x, y) = 0 6y Both partial derivatives vanish at (0, 0); hence (0, 0) is a critical point In addition the Hessian at (0, 0) is 2 2 f (0, 0) = 2 0 This matrix is indefinite: 2 > 0 and = 2 < 0 Therefore f has a saddle point at (0, 0) (b) According to Taylor s formula, near (0, 0) f(x, y) f(0, 0)+ t f (0, 0)(x, y)+ Hence, t (x, y)f (0, 0)(x, y)+ x 2 +2xy+ = (x+y) 2 y 2 + g(t) = f(at, bt) (at + bt) b 2 t 2 + For g to have a minimum at 0, we should try to have g look like a positive quadratic form: the term b 2 t 2 above would then vanish Therefore set a = 1, b = 0 to get g(t) = f(t, 0) = t 2 + t 3 This function clearly has a local minimum at 0 because g (0) = 0 and g (0) = 2 > 0 Therefore a = 1 and b = 0 respond to the question (c) We apply the same argument as above and get: h(t) = f(ct, dt) (ct + dt) 2 d 2 t 2 +
5 This time, we would like to have a local maximum Thus the term (ct + dt) 2 above should vanish To this end we pick c = 1 and d = 1 We get then h(t) = f(t, t) = t 2 2t 2 + t 3 t 3 = t 2 This function clearly has a local maximum at 0, hence c = 1 and d = 1 respond to the problem 5
HW2 - Due 01/30. Each answer must be mathematically justified. Don t forget your name.
HW2 - Due 0/30 Each answer must be mathematically justified. Don t forget your name. Problem. Use the row reduction algorithm to find the inverse of the matrix 0 0, 2 3 5 if it exists. Double check your
More informationChapter 13. Convex and Concave. Josef Leydold Mathematical Methods WS 2018/19 13 Convex and Concave 1 / 44
Chapter 13 Convex and Concave Josef Leydold Mathematical Methods WS 2018/19 13 Convex and Concave 1 / 44 Monotone Function Function f is called monotonically increasing, if x 1 x 2 f (x 1 ) f (x 2 ) It
More information1 Overview. 2 A Characterization of Convex Functions. 2.1 First-order Taylor approximation. AM 221: Advanced Optimization Spring 2016
AM 221: Advanced Optimization Spring 2016 Prof. Yaron Singer Lecture 8 February 22nd 1 Overview In the previous lecture we saw characterizations of optimality in linear optimization, and we reviewed the
More informationMonotone Function. Function f is called monotonically increasing, if. x 1 x 2 f (x 1 ) f (x 2 ) x 1 < x 2 f (x 1 ) < f (x 2 ) x 1 x 2
Monotone Function Function f is called monotonically increasing, if Chapter 3 x x 2 f (x ) f (x 2 ) It is called strictly monotonically increasing, if f (x 2) f (x ) Convex and Concave x < x 2 f (x )
More informationREVIEW OF DIFFERENTIAL CALCULUS
REVIEW OF DIFFERENTIAL CALCULUS DONU ARAPURA 1. Limits and continuity To simplify the statements, we will often stick to two variables, but everything holds with any number of variables. Let f(x, y) be
More informationA A x i x j i j (i, j) (j, i) Let. Compute the value of for and
7.2 - Quadratic Forms quadratic form on is a function defined on whose value at a vector in can be computed by an expression of the form, where is an symmetric matrix. The matrix R n Q R n x R n Q(x) =
More informationHere each term has degree 2 (the sum of exponents is 2 for all summands). A quadratic form of three variables looks as
Reading [SB], Ch. 16.1-16.3, p. 375-393 1 Quadratic Forms A quadratic function f : R R has the form f(x) = a x. Generalization of this notion to two variables is the quadratic form Q(x 1, x ) = a 11 x
More informationThis exam contains 9 problems. CHECK THAT YOU HAVE A COMPLETE EXAM.
Math 126 Final Examination Autumn 2011 Your Name Your Signature Student ID # Quiz Section Professor s Name TA s Name This exam contains 9 problems. CHECK THAT YOU HAVE A COMPLETE EXAM. This exam is closed
More informationMidterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015
Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015 The test lasts 1 hour and 15 minutes. No documents are allowed. The use of a calculator, cell phone or other equivalent electronic
More informationMath 118, Fall 2014 Final Exam
Math 8, Fall 4 Final Exam True or false Please circle your choice; no explanation is necessary True There is a linear transformation T such that T e ) = e and T e ) = e Solution Since T is linear, if T
More informationFunctions of Several Variables
Functions of Several Variables The Unconstrained Minimization Problem where In n dimensions the unconstrained problem is stated as f() x variables. minimize f()x x, is a scalar objective function of vector
More informationEigenvalues and Eigenvectors: An Introduction
Eigenvalues and Eigenvectors: An Introduction The eigenvalue problem is a problem of considerable theoretical interest and wide-ranging application. For example, this problem is crucial in solving systems
More informationSymmetric matrices and dot products
Symmetric matrices and dot products Proposition An n n matrix A is symmetric iff, for all x, y in R n, (Ax) y = x (Ay). Proof. If A is symmetric, then (Ax) y = x T A T y = x T Ay = x (Ay). If equality
More informationMath (P)refresher Lecture 8: Unconstrained Optimization
Math (P)refresher Lecture 8: Unconstrained Optimization September 2006 Today s Topics : Quadratic Forms Definiteness of Quadratic Forms Maxima and Minima in R n First Order Conditions Second Order Conditions
More informationVANDERBILT UNIVERSITY. MATH 2300 MULTIVARIABLE CALCULUS Practice Test 1 Solutions
VANDERBILT UNIVERSITY MATH 2300 MULTIVARIABLE CALCULUS Practice Test 1 Solutions Directions. This practice test should be used as a study guide, illustrating the concepts that will be emphasized in the
More informationCalculus 2502A - Advanced Calculus I Fall : Local minima and maxima
Calculus 50A - Advanced Calculus I Fall 014 14.7: Local minima and maxima Martin Frankland November 17, 014 In these notes, we discuss the problem of finding the local minima and maxima of a function.
More informationECE580 Exam 1 October 4, Please do not write on the back of the exam pages. Extra paper is available from the instructor.
ECE580 Exam 1 October 4, 2012 1 Name: Solution Score: /100 You must show ALL of your work for full credit. This exam is closed-book. Calculators may NOT be used. Please leave fractions as fractions, etc.
More informationHomework sheet 4: EIGENVALUES AND EIGENVECTORS. DIAGONALIZATION (with solutions) Year ? Why or why not? 6 9
Bachelor in Statistics and Business Universidad Carlos III de Madrid Mathematical Methods II María Barbero Liñán Homework sheet 4: EIGENVALUES AND EIGENVECTORS DIAGONALIZATION (with solutions) Year - Is
More informationLINEAR ALGEBRA (PMTH213) Tutorial Questions
Tutorial Questions The tutorial exercises range from revision and routine practice, through lling in details in the notes, to applications of the theory. While the tutorial problems are not compulsory,
More informationPerformance Surfaces and Optimum Points
CSC 302 1.5 Neural Networks Performance Surfaces and Optimum Points 1 Entrance Performance learning is another important class of learning law. Network parameters are adjusted to optimize the performance
More informationMath 3191 Applied Linear Algebra
Math 9 Applied Linear Algebra Lecture 9: Diagonalization Stephen Billups University of Colorado at Denver Math 9Applied Linear Algebra p./9 Section. Diagonalization The goal here is to develop a useful
More information3.5 Quadratic Approximation and Convexity/Concavity
3.5 Quadratic Approximation and Convexity/Concavity 55 3.5 Quadratic Approximation and Convexity/Concavity Overview: Second derivatives are useful for understanding how the linear approximation varies
More informationTest 2 Review Math 1111 College Algebra
Test 2 Review Math 1111 College Algebra 1. Begin by graphing the standard quadratic function f(x) = x 2. Then use transformations of this graph to graph the given function. g(x) = x 2 + 2 *a. b. c. d.
More informationLecture 2 - Unconstrained Optimization Definition[Global Minimum and Maximum]Let f : S R be defined on a set S R n. Then
Lecture 2 - Unconstrained Optimization Definition[Global Minimum and Maximum]Let f : S R be defined on a set S R n. Then 1. x S is a global minimum point of f over S if f (x) f (x ) for any x S. 2. x S
More informationMath 24 Spring 2012 Sample Homework Solutions Week 8
Math 4 Spring Sample Homework Solutions Week 8 Section 5. (.) Test A M (R) for diagonalizability, and if possible find an invertible matrix Q and a diagonal matrix D such that Q AQ = D. ( ) 4 (c) A =.
More informationTranspose & Dot Product
Transpose & Dot Product Def: The transpose of an m n matrix A is the n m matrix A T whose columns are the rows of A. So: The columns of A T are the rows of A. The rows of A T are the columns of A. Example:
More informationMath Abstract Linear Algebra Fall 2011, section E1 Practice Final. This is a (long) practice exam. The real exam will consist of 6 problems.
Math 416 - Abstract Linear Algebra Fall 2011, section E1 Practice Final Name: This is a (long) practice exam. The real exam will consist of 6 problems. In the real exam, no calculators, electronic devices,
More informationAP Calculus Testbank (Chapter 9) (Mr. Surowski)
AP Calculus Testbank (Chapter 9) (Mr. Surowski) Part I. Multiple-Choice Questions n 1 1. The series will converge, provided that n 1+p + n + 1 (A) p > 1 (B) p > 2 (C) p >.5 (D) p 0 2. The series
More informationCHAPTER 4: HIGHER ORDER DERIVATIVES. Likewise, we may define the higher order derivatives. f(x, y, z) = xy 2 + e zx. y = 2xy.
April 15, 2009 CHAPTER 4: HIGHER ORDER DERIVATIVES In this chapter D denotes an open subset of R n. 1. Introduction Definition 1.1. Given a function f : D R we define the second partial derivatives as
More informationMATH 31 - ADDITIONAL PRACTICE PROBLEMS FOR FINAL
MATH 3 - ADDITIONAL PRACTICE PROBLEMS FOR FINAL MAIN TOPICS FOR THE FINAL EXAM:. Vectors. Dot product. Cross product. Geometric applications. 2. Row reduction. Null space, column space, row space, left
More informationCE 191: Civil and Environmental Engineering Systems Analysis. LEC 05 : Optimality Conditions
CE 191: Civil and Environmental Engineering Systems Analysis LEC : Optimality Conditions Professor Scott Moura Civil & Environmental Engineering University of California, Berkeley Fall 214 Prof. Moura
More informationTranspose & Dot Product
Transpose & Dot Product Def: The transpose of an m n matrix A is the n m matrix A T whose columns are the rows of A. So: The columns of A T are the rows of A. The rows of A T are the columns of A. Example:
More informationDEPARTMENT OF MATHEMATICS
DEPARTMENT OF MATHEMATICS Ma322 - Final Exam Spring 2011 May 3,4, 2011 DO NOT TURN THIS PAGE UNTIL YOU ARE INSTRUCTED TO DO SO. Be sure to show all work and justify your answers. There are 8 problems and
More informationFind the indicated derivative. 1) Find y(4) if y = 3 sin x. A) y(4) = 3 cos x B) y(4) = 3 sin x C) y(4) = - 3 cos x D) y(4) = - 3 sin x
Assignment 5 Name Find the indicated derivative. ) Find y(4) if y = sin x. ) A) y(4) = cos x B) y(4) = sin x y(4) = - cos x y(4) = - sin x ) y = (csc x + cot x)(csc x - cot x) ) A) y = 0 B) y = y = - csc
More informationg(t) = f(x 1 (t),..., x n (t)).
Reading: [Simon] p. 313-333, 833-836. 0.1 The Chain Rule Partial derivatives describe how a function changes in directions parallel to the coordinate axes. Now we shall demonstrate how the partial derivatives
More informationPositive Definite Matrix
1/29 Chia-Ping Chen Professor Department of Computer Science and Engineering National Sun Yat-sen University Linear Algebra Positive Definite, Negative Definite, Indefinite 2/29 Pure Quadratic Function
More information8 Extremal Values & Higher Derivatives
8 Extremal Values & Higher Derivatives Not covered in 2016\17 81 Higher Partial Derivatives For functions of one variable there is a well-known test for the nature of a critical point given by the sign
More informationMATH 5720: Unconstrained Optimization Hung Phan, UMass Lowell September 13, 2018
MATH 57: Unconstrained Optimization Hung Phan, UMass Lowell September 13, 18 1 Global and Local Optima Let a function f : S R be defined on a set S R n Definition 1 (minimizers and maximizers) (i) x S
More informationFundamentals of Unconstrained Optimization
dalmau@cimat.mx Centro de Investigación en Matemáticas CIMAT A.C. Mexico Enero 2016 Outline Introduction 1 Introduction 2 3 4 Optimization Problem min f (x) x Ω where f (x) is a real-valued function The
More informationLINEAR ALGEBRA 1, 2012-I PARTIAL EXAM 3 SOLUTIONS TO PRACTICE PROBLEMS
LINEAR ALGEBRA, -I PARTIAL EXAM SOLUTIONS TO PRACTICE PROBLEMS Problem (a) For each of the two matrices below, (i) determine whether it is diagonalizable, (ii) determine whether it is orthogonally diagonalizable,
More informationTopic 2 Quiz 2. choice C implies B and B implies C. correct-choice C implies B, but B does not imply C
Topic 1 Quiz 1 text A reduced row-echelon form of a 3 by 4 matrix can have how many leading one s? choice must have 3 choice may have 1, 2, or 3 correct-choice may have 0, 1, 2, or 3 choice may have 0,
More informationTangent spaces, normals and extrema
Chapter 3 Tangent spaces, normals and extrema If S is a surface in 3-space, with a point a S where S looks smooth, i.e., without any fold or cusp or self-crossing, we can intuitively define the tangent
More informationReview problems for MA 54, Fall 2004.
Review problems for MA 54, Fall 2004. Below are the review problems for the final. They are mostly homework problems, or very similar. If you are comfortable doing these problems, you should be fine on
More informationx 3y 2z = 6 1.2) 2x 4y 3z = 8 3x + 6y + 8z = 5 x + 3y 2z + 5t = 4 1.5) 2x + 8y z + 9t = 9 3x + 5y 12z + 17t = 7
Linear Algebra and its Applications-Lab 1 1) Use Gaussian elimination to solve the following systems x 1 + x 2 2x 3 + 4x 4 = 5 1.1) 2x 1 + 2x 2 3x 3 + x 4 = 3 3x 1 + 3x 2 4x 3 2x 4 = 1 x + y + 2z = 4 1.4)
More informationCS 323: Numerical Analysis and Computing
CS 323: Numerical Analysis and Computing MIDTERM #2 Instructions: This is an open notes exam, i.e., you are allowed to consult any textbook, your class notes, homeworks, or any of the handouts from us.
More informationLinear Algebra. Chapter 8: Eigenvalues: Further Applications and Computations Section 8.2. Applications to Geometry Proofs of Theorems.
Linear Algebra Chapter 8: Eigenvalues: Further Applications and Computations Section 8.2. Applications to Geometry Proofs of Theorems May 1, 2018 () Linear Algebra May 1, 2018 1 / 8 Table of contents 1
More informationAMS Foundations Exam - Part A, January 2018
AMS Foundations Exam - Part A, January 2018 Name: ID Num. Part A: / 75 Part B: / 75 Total: / 150 This component of the exam (Part A) consists of two sections (Linear Algebra and Advanced Calculus) with
More informationLecture 8: Maxima and Minima
Lecture 8: Maxima and Minima Rafikul Alam Department of Mathematics IIT Guwahati Local extremum of f : R n R Let f : U R n R be continuous, where U is open. Then f has a local maximum at p if there exists
More informationSolutions to Final Exam Sample Problems, Math 246, Spring 2011
Solutions to Final Exam Sample Problems, Math 246, Spring 2 () Consider the differential equation dy dt = (9 y2 )y 2 (a) Identify its equilibrium (stationary) points and classify their stability (b) Sketch
More informationFinal Exam. Linear Algebra Summer 2011 Math S2010X (3) Corrin Clarkson. August 10th, Solutions
Final Exam Linear Algebra Summer Math SX (3) Corrin Clarkson August th, Name: Solutions Instructions: This is a closed book exam. You may not use the textbook, notes or a calculator. You will have 9 minutes
More informationI II III IV V VI VII VIII IX Total
DEPARTMENT OF MATHEMATICS AND STATISTICS QUEEN S UNIVERSITY AT KINGSTON MATH 121 - DEC 2014 CDS/Section 700 Students ONLY INSTRUCTIONS: Answer all questions, writing clearly in the space provided. If you
More informationUNIVERSITY OF SOUTHAMPTON. A foreign language dictionary (paper version) is permitted provided it contains no notes, additions or annotations.
UNIVERSITY OF SOUTHAMPTON MATH055W SEMESTER EXAMINATION 03/4 MATHEMATICS FOR ELECTRONIC & ELECTRICAL ENGINEERING Duration: 0 min Solutions Only University approved calculators may be used. A foreign language
More informationLECTURE 22: SWARM INTELLIGENCE 3 / CLASSICAL OPTIMIZATION
15-382 COLLECTIVE INTELLIGENCE - S19 LECTURE 22: SWARM INTELLIGENCE 3 / CLASSICAL OPTIMIZATION TEACHER: GIANNI A. DI CARO WHAT IF WE HAVE ONE SINGLE AGENT PSO leverages the presence of a swarm: the outcome
More informationAP Calculus BC Fall Final Part IIa
AP Calculus BC 18-19 Fall Final Part IIa Calculator Required Name: 1. At time t = 0, there are 120 gallons of oil in a tank. During the time interval 0 t 10 hours, oil flows into the tank at a rate of
More informationLinear Systems. Class 27. c 2008 Ron Buckmire. TITLE Projection Matrices and Orthogonal Diagonalization CURRENT READING Poole 5.4
Linear Systems Math Spring 8 c 8 Ron Buckmire Fowler 9 MWF 9: am - :5 am http://faculty.oxy.edu/ron/math//8/ Class 7 TITLE Projection Matrices and Orthogonal Diagonalization CURRENT READING Poole 5. Summary
More informationMath 207 Honors Calculus III Final Exam Solutions
Math 207 Honors Calculus III Final Exam Solutions PART I. Problem 1. A particle moves in the 3-dimensional space so that its velocity v(t) and acceleration a(t) satisfy v(0) = 3j and v(t) a(t) = t 3 for
More informationChapter 7. Extremal Problems. 7.1 Extrema and Local Extrema
Chapter 7 Extremal Problems No matter in theoretical context or in applications many problems can be formulated as problems of finding the maximum or minimum of a function. Whenever this is the case, advanced
More informationLINEAR 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 information18.06 Problem Set 8 Solution Due Wednesday, 22 April 2009 at 4 pm in Total: 160 points.
86 Problem Set 8 Solution Due Wednesday, April 9 at 4 pm in -6 Total: 6 points Problem : If A is real-symmetric, it has real eigenvalues What can you say about the eigenvalues if A is real and anti-symmetric
More information0, otherwise. Find each of the following limits, or explain that the limit does not exist.
Midterm Solutions 1, y x 4 1. Let f(x, y) = 1, y 0 0, otherwise. Find each of the following limits, or explain that the limit does not exist. (a) (b) (c) lim f(x, y) (x,y) (0,1) lim f(x, y) (x,y) (2,3)
More informationOR 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 informationx +3y 2t = 1 2x +y +z +t = 2 3x y +z t = 7 2x +6y +z +t = a
UCM Final Exam, 05/8/014 Solutions 1 Given the parameter a R, consider the following linear system x +y t = 1 x +y +z +t = x y +z t = 7 x +6y +z +t = a (a (6 points Discuss the system depending on the
More informationSection 7.3: SYMMETRIC MATRICES AND ORTHOGONAL DIAGONALIZATION
Section 7.3: SYMMETRIC MATRICES AND ORTHOGONAL DIAGONALIZATION When you are done with your homework you should be able to Recognize, and apply properties of, symmetric matrices Recognize, and apply properties
More informationLecture 6 Positive Definite Matrices
Linear Algebra Lecture 6 Positive Definite Matrices Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Spring 2017 2017/6/8 Lecture 6: Positive Definite Matrices
More informationMathematical Economics. Lecture Notes (in extracts)
Prof. Dr. Frank Werner Faculty of Mathematics Institute of Mathematical Optimization (IMO) http://math.uni-magdeburg.de/ werner/math-ec-new.html Mathematical Economics Lecture Notes (in extracts) Winter
More informationMathematical MCQ for international students admitted to École polytechnique
Mathematical MCQ for international students admitted to École polytechnique This multiple-choice questionnaire is intended for international students admitted to the first year of the engineering program
More informationExercise Sheet 1.
Exercise Sheet 1 You can download my lecture and exercise sheets at the address http://sami.hust.edu.vn/giang-vien/?name=huynt 1) Let A, B be sets. What does the statement "A is not a subset of B " mean?
More informationChapter 6. Eigenvalues. Josef Leydold Mathematical Methods WS 2018/19 6 Eigenvalues 1 / 45
Chapter 6 Eigenvalues Josef Leydold Mathematical Methods WS 2018/19 6 Eigenvalues 1 / 45 Closed Leontief Model In a closed Leontief input-output-model consumption and production coincide, i.e. V x = x
More informationCalculus for the Life Sciences II Assignment 6 solutions. f(x, y) = 3π 3 cos 2x + 2 sin 3y
Calculus for the Life Sciences II Assignment 6 solutions Find the tangent plane to the graph of the function at the point (0, π f(x, y = 3π 3 cos 2x + 2 sin 3y Solution: The tangent plane of f at a point
More informationDO NOT WRITE ABOVE THIS LINE!! MATH 181 Final Exam. December 8, 2016
MATH 181 Final Exam December 8, 2016 Directions. Fill in each of the lines below. Circle your instructor s name and write your TA s name. Then read the directions that follow before beginning the exam.
More information1 Last time: least-squares problems
MATH Linear algebra (Fall 07) Lecture Last time: least-squares problems Definition. If A is an m n matrix and b R m, then a least-squares solution to the linear system Ax = b is a vector x R n such that
More informationWe start by computing the characteristic polynomial of A as. det (A λi) = det. = ( 2 λ)(1 λ) (2)(2) = (λ 2)(λ + 3)
Let A [ 2 2 2 Compute the eigenvalues and eigenspaces of A We start b computing the characteristic polnomial of A as [ 2 λ 2 det (A λi) det 2 λ ( 2 λ)( λ) (2)(2) λ 2 + λ 2 4 λ 2 + λ 6 (λ 2)(λ + 3) The
More informationMATH 251 Examination II April 3, 2017 FORM A. Name: Student Number: Section:
MATH 251 Examination II April 3, 2017 FORM A Name: Student Number: Section: This exam has 12 questions for a total of 100 points. In order to obtain full credit for partial credit problems, all work must
More informationMATH 115A: SAMPLE FINAL SOLUTIONS
MATH A: SAMPLE FINAL SOLUTIONS JOE HUGHES. Let V be the set of all functions f : R R such that f( x) = f(x) for all x R. Show that V is a vector space over R under the usual addition and scalar multiplication
More informationFIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS III: Autonomous Planar Systems David Levermore Department of Mathematics University of Maryland
FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS III: Autonomous Planar Systems David Levermore Department of Mathematics University of Maryland 4 May 2012 Because the presentation of this material
More informationExtreme Values and Positive/ Negative Definite Matrix Conditions
Extreme Values and Positive/ Negative Definite Matrix Conditions James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University November 8, 016 Outline 1
More informationDIAGONALIZATION. In order to see the implications of this definition, let us consider the following example Example 1. Consider the matrix
DIAGONALIZATION Definition We say that a matrix A of size n n is diagonalizable if there is a basis of R n consisting of eigenvectors of A ie if there are n linearly independent vectors v v n such that
More informationMATH The Chain Rule Fall 2016 A vector function of a vector variable is a function F: R n R m. In practice, if x 1, x n is the input,
MATH 20550 The Chain Rule Fall 2016 A vector function of a vector variable is a function F: R n R m. In practice, if x 1, x n is the input, F(x 1,, x n ) F 1 (x 1,, x n ),, F m (x 1,, x n ) where each
More informationEconomics 205, Fall 2002: Final Examination, Possible Answers
Economics 05, Fall 00: Final Examination, Possible Answers Comments on the Exam Grades: 43 possible; high: 413; median: 34; low: 36 I was generally happy with the answers to questions 3-8, satisfied with
More informationMath 2: Algebra 2, Geometry and Statistics Ms. Sheppard-Brick Chapter 4 Test Review
Chapter 4 Test Review Students will be able to (SWBAT): Write an explicit and a recursive function rule for a linear table of values. Write an explicit function rule for a quadratic table of values. Determine
More informationQuadratic forms. Here. Thus symmetric matrices are diagonalizable, and the diagonalization can be performed by means of an orthogonal matrix.
Quadratic forms 1. Symmetric matrices An n n matrix (a ij ) n ij=1 with entries on R is called symmetric if A T, that is, if a ij = a ji for all 1 i, j n. We denote by S n (R) the set of all n n symmetric
More informationMA102: Multivariable Calculus
MA102: Multivariable Calculus Rupam Barman and Shreemayee Bora Department of Mathematics IIT Guwahati Differentiability of f : U R n R m Definition: Let U R n be open. Then f : U R n R m is differentiable
More informationMath 203A - Solution Set 1
Math 203A - Solution Set 1 Problem 1. Show that the Zariski topology on A 2 is not the product of the Zariski topologies on A 1 A 1. Answer: Clearly, the diagonal Z = {(x, y) : x y = 0} A 2 is closed in
More informationSolutions to Homework 7
Solutions to Homework 7 Exercise #3 in section 5.2: A rectangular box is inscribed in a hemisphere of radius r. Find the dimensions of the box of maximum volume. Solution: The base of the rectangular box
More informationMATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION
MATH (LINEAR ALGEBRA ) FINAL EXAM FALL SOLUTIONS TO PRACTICE VERSION Problem (a) For each matrix below (i) find a basis for its column space (ii) find a basis for its row space (iii) determine whether
More information2. Linear algebra. matrices and vectors. linear equations. range and nullspace of matrices. function of vectors, gradient and Hessian
FE661 - Statistical Methods for Financial Engineering 2. Linear algebra Jitkomut Songsiri matrices and vectors linear equations range and nullspace of matrices function of vectors, gradient and Hessian
More informationFinal Exam - Take Home Portion Math 211, Summer 2017
Final Exam - Take Home Portion Math 2, Summer 207 Name: Directions: Complete a total of 5 problems. Problem must be completed. The remaining problems are categorized in four groups. Select one problem
More informationMATH 1553-C MIDTERM EXAMINATION 3
MATH 553-C MIDTERM EXAMINATION 3 Name GT Email @gatech.edu Please read all instructions carefully before beginning. Please leave your GT ID card on your desk until your TA scans your exam. Each problem
More informationAPPLICATIONS The eigenvalues are λ = 5, 5. An orthonormal basis of eigenvectors consists of
CHAPTER III APPLICATIONS The eigenvalues are λ =, An orthonormal basis of eigenvectors consists of, The eigenvalues are λ =, A basis of eigenvectors consists of, 4 which are not perpendicular However,
More information, b = 0. (2) 1 2 The eigenvectors of A corresponding to the eigenvalues λ 1 = 1, λ 2 = 3 are
Quadratic forms We consider the quadratic function f : R 2 R defined by f(x) = 2 xt Ax b T x with x = (x, x 2 ) T, () where A R 2 2 is symmetric and b R 2. We will see that, depending on the eigenvalues
More information2.6 Logarithmic Functions. Inverse Functions. Question: What is the relationship between f(x) = x 2 and g(x) = x?
Inverse Functions Question: What is the relationship between f(x) = x 3 and g(x) = 3 x? Question: What is the relationship between f(x) = x 2 and g(x) = x? Definition (One-to-One Function) A function f
More informationMath Matrix Algebra
Math 44 - Matrix Algebra Review notes - (Alberto Bressan, Spring 7) sec: Orthogonal diagonalization of symmetric matrices When we seek to diagonalize a general n n matrix A, two difficulties may arise:
More informationMath 18, Linear Algebra, Lecture C00, Spring 2017 Review and Practice Problems for Final Exam
Math 8, Linear Algebra, Lecture C, Spring 7 Review and Practice Problems for Final Exam. The augmentedmatrix of a linear system has been transformed by row operations into 5 4 8. Determine if the system
More informationPaper Specific Instructions
Paper Specific Instructions. The examination is of 3 hours duration. There are a total of 60 questions carrying 00 marks. The entire paper is divided into three sections, A, B and C. All sections are compulsory.
More informationNumerical Optimization
Numerical Optimization Unit 2: Multivariable optimization problems Che-Rung Lee Scribe: February 28, 2011 (UNIT 2) Numerical Optimization February 28, 2011 1 / 17 Partial derivative of a two variable function
More informationIntroduction to Unconstrained Optimization: Part 2
Introduction to Unconstrained Optimization: Part 2 James Allison ME 555 January 29, 2007 Overview Recap Recap selected concepts from last time (with examples) Use of quadratic functions Tests for positive
More information3.7 Constrained Optimization and Lagrange Multipliers
3.7 Constrained Optimization and Lagrange Multipliers 71 3.7 Constrained Optimization and Lagrange Multipliers Overview: Constrained optimization problems can sometimes be solved using the methods of the
More informationMath 23 Practice Quiz 2018 Spring
1. Write a few examples of (a) a homogeneous linear differential equation (b) a non-homogeneous linear differential equation (c) a linear and a non-linear differential equation. 2. Calculate f (t). Your
More informationThe Derivative. Appendix B. B.1 The Derivative of f. Mappings from IR to IR
Appendix B The Derivative B.1 The Derivative of f In this chapter, we give a short summary of the derivative. Specifically, we want to compare/contrast how the derivative appears for functions whose domain
More informationEXERCISES 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