Designing Information Devices and Systems I Discussion 4B

Similar documents
Designing Information Devices and Systems I Discussion 4B

Designing Information Devices and Systems I Summer 2017 D. Aranki, F. Maksimovic, V. Swamy Midterm 1. Exam Location: 2050 VLSB

Designing Information Devices and Systems I Fall 2018 Homework 5

Lecture 15, 16: Diagonalization

Designing Information Devices and Systems I Spring 2019 Homework 5

Designing Information Devices and Systems I Fall 2018 Lecture Notes Note 6

Chapter 5. Eigenvalues and Eigenvectors

Final. for Math 308, Winter This exam contains 7 questions for a total of 100 points in 15 pages.

Designing Information Devices and Systems I Fall 2018 Homework 3

LINEAR ALGEBRA 1, 2012-I PARTIAL EXAM 3 SOLUTIONS TO PRACTICE PROBLEMS

Warm-up. True or false? Baby proof. 2. The system of normal equations for A x = y has solutions iff A x = y has solutions

Section 6.4. The Gram Schmidt Process

Examples True or false: 3. Let A be a 3 3 matrix. Then there is a pattern in A with precisely 4 inversions.

Designing Information Devices and Systems I Fall 2018 Lecture Notes Note 6

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 6

CS 246 Review of Linear Algebra 01/17/19

5.3.5 The eigenvalues are 3, 2, 3 (i.e., the diagonal entries of D) with corresponding eigenvalues. Null(A 3I) = Null( ), 0 0

235 Final exam review questions

Math 2B Spring 13 Final Exam Name Write all responses on separate paper. Show your work for credit.

Elementary Linear Algebra Review for Exam 3 Exam is Friday, December 11th from 1:15-3:15

2. Every linear system with the same number of equations as unknowns has a unique solution.

Eigenvalues and Eigenvectors

Review problems for MA 54, Fall 2004.

Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015

Math 18, Linear Algebra, Lecture C00, Spring 2017 Review and Practice Problems for Final Exam

Question: Given an n x n matrix A, how do we find its eigenvalues? Idea: Suppose c is an eigenvalue of A, then what is the determinant of A-cI?

ANALYTICAL MATHEMATICS FOR APPLICATIONS 2018 LECTURE NOTES 3

Math 3191 Applied Linear Algebra

Chapters 5 & 6: Theory Review: Solutions Math 308 F Spring 2015

Linear Algebra Exercises

Problems for M 10/26:

Designing Information Devices and Systems I Fall 2016 Babak Ayazifar, Vladimir Stojanovic Final Exam

Name Solutions Linear Algebra; Test 3. Throughout the test simplify all answers except where stated otherwise.

Linear Algebra Practice Problems

Problem # Max points possible Actual score Total 120

and let s calculate the image of some vectors under the transformation T.

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions

REVIEW FOR EXAM III SIMILARITY AND DIAGONALIZATION

4. Linear transformations as a vector space 17

Solutions to Final Practice Problems Written by Victoria Kala Last updated 12/5/2015

Designing Information Devices and Systems I Spring 2018 Homework 5

(a) II and III (b) I (c) I and III (d) I and II and III (e) None are true.

Math 1553, Introduction to Linear Algebra

Recall : Eigenvalues and Eigenvectors

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017

Matrix multiplications that do row operations

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION

Eigenvalues and Eigenvectors

Matrices related to linear transformations

Eigenvalue and Eigenvector Homework

Announcements Monday, October 29

MATH 221, Spring Homework 10 Solutions

Solutions to Review Problems for Chapter 6 ( ), 7.1

Remark By definition, an eigenvector must be a nonzero vector, but eigenvalue could be zero.

SOLUTIONS: ASSIGNMENT Use Gaussian elimination to find the determinant of the matrix. = det. = det = 1 ( 2) 3 6 = 36. v 4.

Practice problems for Exam 3 A =

[Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty.]

Econ Slides from Lecture 7

ft-uiowa-math2550 Assignment OptionalFinalExamReviewMultChoiceMEDIUMlengthForm due 12/31/2014 at 10:36pm CST

Designing Information Devices and Systems I Spring 2016 Official Lecture Notes Note 21

Sample Final Exam: Solutions

MATH 31 - ADDITIONAL PRACTICE PROBLEMS FOR FINAL

First of all, the notion of linearity does not depend on which coordinates are used. Recall that a map T : R n R m is linear if

Final Review Written by Victoria Kala SH 6432u Office Hours R 12:30 1:30pm Last Updated 11/30/2015

Cheat Sheet for MATH461

Preliminary/Qualifying Exam in Numerical Analysis (Math 502a) Spring 2012

Math 314/ Exam 2 Blue Exam Solutions December 4, 2008 Instructor: Dr. S. Cooper. Name:

MATH 315 Linear Algebra Homework #1 Assigned: August 20, 2018

I. Multiple Choice Questions (Answer any eight)

18.06 Quiz 2 April 7, 2010 Professor Strang

EXAM. Exam 1. Math 5316, Fall December 2, 2012

Math Fall Final Exam

Math 308 Practice Final Exam Page and vector y =

Practice Final Exam Solutions

Exercise Set 7.2. Skills

v = 1(1 t) + 1(1 + t). We may consider these components as vectors in R n and R m : w 1. R n, w m

Linear algebra I Homework #1 due Thursday, Oct Show that the diagonals of a square are orthogonal to one another.

Jordan Normal Form and Singular Decomposition

Math 20F Practice Final Solutions. Jor-el Briones

Problem 1: Solving a linear equation

1 Inner Product and Orthogonality

4 ORTHOGONALITY ORTHOGONALITY OF THE FOUR SUBSPACES 4.1

18.06SC Final Exam Solutions

1 Introduction. 2 Determining what the J i blocks look like. December 6, 2006

Numerical Linear Algebra Homework Assignment - Week 2

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 10

Remark 1 By definition, an eigenvector must be a nonzero vector, but eigenvalue could be zero.

Final Exam Practice Problems Answers Math 24 Winter 2012

More chapter 3...linear dependence and independence... vectors

Problems for M 11/2: A =

Review of Linear Algebra

MATH 223 FINAL EXAM APRIL, 2005

EXAM. Exam #3. Math 2360, Spring April 24, 2001 ANSWERS

Linear Algebra. and

MATH 310, REVIEW SHEET 2

ICS 6N Computational Linear Algebra Eigenvalues and Eigenvectors

Math Final December 2006 C. Robinson

Agenda: Understand the action of A by seeing how it acts on eigenvectors.

Study Guide for Linear Algebra Exam 2

Problem Set 9 Due: In class Tuesday, Nov. 27 Late papers will be accepted until 12:00 on Thursday (at the beginning of class).

Transcription:

0.5 0.4 0.4 0.4 Last Updated: 2018-09-19 23:58 1 EECS 16A Fall 2018 Designing Information Devices and Systems I Discussion 4B Reference Definitions: Orthogonality n n matrix A: We ve seen that the following statements are equivalent for an A is invertible The equation A x = 0, has a unique solution, which is x = 0 The columns of A are linearly independent For each column vector b R n, A x = b has a unique solution x Null(A) = 0 Conversely, the opposites are equivalent statements: A is not invertible A x = 0 for some x 0 The columns of A are linearly dependent There is not be a unique x for every b where A x = b Null(A) contains more than just the zero vector 0 These are part of what is known as the Invertible Matrix Theorem. 1. Steady State Reservoir Levels We have 3 reservoirs: A,B and C. The pumps system between the reservoirs is depicted in Figure 1. 0.2 A B 0.3 0.2 0.3 C 0.3 Figure 1: Reservoir pumps system. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 1

Last Updated: 2018-09-19 23:58 2 (a) Write out the transition matrix representing the pumps system. (b) Assuming that you start the pumps with the water levels of the reservoirs at A 0 = 129,B 0 = 109,C 0 = 0 (in kiloliters), what would be the steady state water levels (in kiloliters) according to the pumps system described above? Hint: If x ss = A ss B ss C ss is a vector describing the steady state levels of water in the reservoirs (in kiloliters), what happens if you fill the reservoirs A,B and C with A ss,b ss and C ss kiloliters of water, respectively, and apply the pumps once? Hint II: Note that the pumps system preserves the total amount of water in the reservoirs. That is, no water is lost or gained by applying the pumps. 2. Mechanical Eigenvalues and Eigenvectors In each part, find the eigenvalues of the matrix M and the associated eigenvectors. [ ] 1 0 (a) M = 0 9 [ ] 1 1 (b) M = 2 2 0 0 0 (c) (PRACTICE) M = 3 4 9 0 0 3 [ ] 0 1 (d) (PRACTICE) M = 1 0 3. Mechanical Determinants [ ] 2 0 (a) Compute the determinant of. 0 3 [ ] 2 1 (b) Compute the determinant of. 0 3 4 0 0 0 (c) Compute the determinant of 0 17 0 0 0 0 31 0. 0 0 0 2 4. Row Operations and Determinants In this question we explore the effect of row operations on the determinant of a matrix. Note that scaling a row by a will increase the determinant by a factor of a, and adding a multiple of one row to another will not change the determinant. Swapping two rows of a matrix and computing the determinant is equivalent to multiplying the determinant of the original matrix by 1. The determinant of an identity matrix is 1. Feel free to prove these properties to convince yourself that they hold for general square matrices. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 2

Last Updated: 2018-09-19 23:58 3 (a) An upper triangular matrix is a matrix with zeros below its diagonal. For example a 3 3 upper triangular matrix is: a 1 a 2 a 3 0 b 2 b 3 0 0 c 3 By considering row operations and what they do to the determinant, argue that the determinant of a general n n upper triangular matrix is the product of its diagonal entries if they are non-zero. For example, the determinant of the 3 3 matrix above is a 1 b 2 c 3 if a 1,b 2,c 3 0. (b) If the diagonal of an upper-triangular matrix has a zero entry, argue that its determinant is still the product of its diagonal entries. 5. (PRACTICE) StateRank Car Rentals You are an analyst at StateRank Car Rentals, which operates in California, Oregon, and Nevada. You are hired to analyze the number of rental cars going into and out of each of the three states (CA, OR, and NV). s CA [n] The number of cars in each state on day n {0,1,...} can be represented by the state vector s[n] = s OR [n]. s NV [n] The state vector follows the state evolution equation s[n + 1] = A s[n], n {0, 1,...}, where the transition matrix, A, of this linear dynamic system is A = (a) Use the designated boxes in Figure 2 to fill in the weights for the daily travel dynamics of rental cars between the three states, as described by the state transition matrix A. Note the order of the elements in the state vector s[n]. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 3

Last Updated: 2018-09-19 23:58 4 CA OR NV Figure 2: StateRank Rental Cars Daily Travel Dynamics. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 4

Last Updated: 2018-09-19 23:58 5 A copy of the state transition matrix for reference: A = 100 (b) Suppose the state vector on day n = 4 is s[4] = 200. Calculate the state vector on day 5, s[5]. 100 (c) We want to express the number of cars in each state on day n as a function of the initial number of cars in each state on day 0. That is, we write s[n] in terms of s[0] as follows: Express the matrix B in terms of A and n. s[n] = B s[0] UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 5

Last Updated: 2018-09-19 23:58 6 A copy of the state transition matrix for reference: A = (d) We denote the eigenvalue/eigenvector pairs of the matrix A by 50 0 10 λ 1 = 1, u 1 = 40, λ 2, u 2 = 10, and λ 3, u 3 = 0. 110 10 10 Find the eigenvalues λ 2 and λ 3 corresponding to the eigenvectors u 2 and u 3, respectively. Note that since λ 1 = 1 is given, you don t have to calculate it. (e) For the given dynamics in this problem, does a matrix C exists such that s[n 1] = C s[n], for n {1,2,...}? Justify your answer. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 6

Last Updated: 2018-09-19 23:58 7 A copy of the state transition matrix for reference: A = (f) Suppose that the initial number of rental cars in each state on day 0 is 7000 s[0] = 5000 = 100 u 1 100 u 2 200 u 3, 8000 where u 1, u 2 and u 3 are the eigenvectors from part (d). After a very large number of days n, how many rental cars will there be in each state? That is, i) calculate s = lim n s[n] and ii) show that the system will indeed converge to s as n if it starts from s[0]. Hint: If you didn t solve part (d), the eigenvalues satisfy λ 1 = 1, λ 2 < 1 and λ 3 < 1. UCB EECS 16A, Fall 2018, Discussion 4B, All Rights Reserved. This may not be publicly shared without explicit permission. 7