Designing Information Devices and Systems I Spring 2018 Midterm 1. Exam Location: 155 Dwinelle Last Name: Cheng - Lazich

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EECS 16A Designing Information Devices and Systems I Spring 2018 Midterm 1 Exam Location: 155 Dwinelle Last Name: Cheng - Lazich PRINT your student ID: PRINT AND SIGN your name:, (last name) (first name) (signature) PRINT your discussion section and GSI(s) (the one you attend): Name and SID of the person to your left: Name and SID of the person to your right: Name and SID of the person in front of you: Name and SID of the person behind you: 1. What did you do over winter break? (1 Point) 2. What activity do you really enjoy? (1 Point) Do not turn this page until the proctor tells you to do so. You may work on the questions above. EECS 16A, Spring 2018, Midterm 1 1

3. System of Equations (4 points) Solve the following system of equations using Gaussian elimination. If there is no solution, explain why. x + 3y z = 4 4x y + 2z = 8 2x 7y + 4z = 3 EECS 16A, Spring 2018, Midterm 1 2

4. Eig-dentical Eigenvalues (10 points) (a) (2 points) Consider the following matrix: [ ] 2 1 A = 1 a [ ] 3 Is v = in the column space of A when a = 3? Justify your answer in 1-2 sentences. 8 (b) (8 points) Solve for the value of a that yields the smallest possible identical eigenvalues for the matrix A. EECS 16A, Spring 2018, Midterm 1 3

5. Nullspace (8 points) 1 0 4 M = 1 2 6 0 1 x (a) (3 points) Find all the values for x such that M has a trivial nullspace (this means that the nullspace contains only the zero vector). (b) (5 points) Find a value for x such that it has a nontrivial nullspace and solve for the nullspace. EECS 16A, Spring 2018, Midterm 1 4

6. Vectors and Bases and Spans, Oh My! (6 points) 1 2 A = 2, 8 3 5 4 0 0 0 5 B = 0, 0, 3, 0, 3 0 2 0 0 2 3 1 2 2 0 C = 1, 2, 0 2 2 0 0 1 2 0.5 1.5 D = 4.5, 0, 4.5 5 3.75 1.25 (a) (2 points) Select from (A), (B), (C), (D) all sets of vectors above that span R 3, and write their corresponding letter below. If none span R 3, write "none". (b) (2 points) Select from (A), (B), (C), (D) all sets of vectors above that form a basis for R 3, and write their corresponding letter below. If none form a basis for R 3, write "none". (c) (2 points) Can a set that contains the zero vector ever be a basis for R n? Explain in one or two sentences why or why not. EECS 16A, Spring 2018, Midterm 1 5

7. Proofs! Oh null! (10 points) (a) (3 points) Show that if x Null(A) then A x + A 2 x + + A n x = 0. (b) (4 points) Suppose we have a square matrix A with full rank and a matrix B. Show that Null(AB) = Null(B). (c) (3 points) Conceptually, if a state-transition matrix has a non-trivial nullspace (i.e. non-zero) is the information about previous states preserved? Circle your answer, then give 1-2 sentences of justification. Yes No Sometimes EECS 16A, Spring 2018, Midterm 1 6

8. Linear Algebra in a Pinch! (16 points) As you look at your smartphone to get Google Maps directions to TeaOne in Cory Hall, you realize that your smartphone is doing exactly what you do in class linear algebra! As your fingers apply gestures to the screen, the phone is performing matrix transformations on the screen image. In the following parts, we represent coordinates before transformation as x = [ ] T x 1 x 2 and coordinates after transformation as x = [ x 1 x 2] T. Although specific points are labeled, the transformation applies to all points in the (x 1,x 2 ) plane. (a) (5 points) You pinch the screen to zoom out, as shown in the figure below: The point represented by a dot moves from (0,3) to (0,2), and the point represented by a star moves from ( 3, 1.5) to ( 2, 1). What is the transformation matrix, A, such that x = A x for this transformation? EECS 16A, Spring 2018, Midterm 1 7

(b) (5 points) Smartphones are smart, so if you rotate your phone, the map will reorient itself to make sure you can read it! That is, if you rotate your phone 90 clockwise, the map will rotate 90 counter-clockwise relative to the phone, as shown below. The point represented by a dot moves from (0,3) to ( 3,0), and the point represented by a star moves from ( 3, 1.5) to (1.5, 3). What is the transformation matrix, R, such that x = R x for this transformation? EECS 16A, Spring 2018, Midterm 1 8

(c) (6 points) So far, we have only done transformations that involve rotation and scaling, but another key feature of Google Maps is that we can scroll laterally across a map, as shown below. The point represented by a dot moves from (0,2) to (2,2), and the point represented by a star moves from ( 2, 1) to (0, 1). In the previous parts we were able to represent the map transformations in the form x = A x + b (Previously b = 0.) What are A and b for the scrolling operation above? Is this a linear transformation? EECS 16A, Spring 2018, Midterm 1 9

9. Mining Population (20 points) There is a population of cryptocurrency miners. These miners are primarily interested in two coins: Oski- Coin and BearCoin, and they switch between mining the two coins in a predictable way. Every week, 20% of OskiCoin miners switch to BearCoin and 30% of BearCoin miners switch to OskiCoin. The remaining miners keep mining the same coin for the following week. Let s 1 [n] be the number of miners of OskiCoin on week n and s 2 [n] be the number of miners of BearCoin on week n. s[n] = [ ] s1 [n] s 2 [n] (a) (2 points) Draw a well-labeled directed graph showing how the population of miners changes each week. Be sure to label each node and place appropriate weights on each edge. (b) (2 points) Determine the state transition matrix A. EECS 16A, Spring 2018, Midterm 1 10

(c) (5 points) Find the eigenvalues (λ 1...λ n ) and eigenvectors ( v 1... v n ) of A. EECS 16A, Spring 2018, Midterm 1 11

(d) (5 points) Express [ ] 5 in the coordinate system of the eigenvectors, V = { v 0 1,..., v n }. (e) (6 points) If we start with 1000 miners mining OskiCoin and 0 miners mining BearCoin, then what will the steady state distribution of miners be? EECS 16A, Spring 2018, Midterm 1 12

10. Bad Barometers (20 points) Two scientists, Alice and Bob, want to determine the air pressure at the bottom and the top of Mt. Diablo. They know that pressure changes linearly with altitude. We represent the air pressure at the top and bottom of the mountain as a vector: [ ] pbottom p = Scientist Alice first takes a pressure measurement at the bottom of the mountain. Then she starts hiking up. 10% of the way up she she takes a second measurement. She knows she can invert her system of equations, so she turns around. We can represent Alice s measurements as [ ] 1 0 m a = A a p where A a = 0.9 0.1 Scientist Bob also takes a pressure measurement at the bottom of the mountain. He starts hiking and is enjoying the view so he hikes 50% of the way to the top where he stops and takes a second measurement. We can represent Bob s measurements as [ ] 1 0 m b = A b p where A b = 0.5 0.5 Unfortunately, both scientists have old barometers that don t work very well, so rather than measuring the true pressure, they measure the pressure plus some offset, s. We define q to be the calculated pressure based on the inaccurate measurement: m a + s a = A a q a p top m b + s b = A b q b We are interested in the error, e, which is the difference between the true pressure and the calculated pressure: e a = q a p e b = q b p (a) (4 points) Determine an expression for e a as a function of A a and s a. EECS 16A, Spring 2018, Midterm 1 13

[ ] 1 (b) (6 points) Suppose that s a = s b =. This means that our scientists measure pressure that is 1 kpa too 1 low in their first measurement and 1 kpa too high in their second measurement. (Both scientist have very similar old barometers, so they have the same offset for both measurements.) Calculate Alice s error, e a, and Bob s error, e b. EECS 16A, Spring 2018, Midterm 1 14

(c) (6 points) Consider a general invertible, diagonalizable measurement matrix A R n n with eigenvalues λ 1...λ n and corresponding eigenvectors v 1... v n, and a general offset vector s R n. Show that e = n i=1 where α 1...α n are scalar values such that n i=1 α i v i = s. α i λ i v i (d) (4 points) You calculate the eigenvalues and eigenvectors for A a and A b to be the following: A a A b λ 1 = 1 λ 1 = 1 λ 2 = [ 0.1 ] [ ] λ 2 = [ 0.5 ] 0 1 0 v 1 = v 1 2 = v 1 1 = 1 [ ] 1 v 2 = 1 Based on the equation in Part (c) and the eigenvalues and eigenvectors above, which matrix (A a or A b ) is more sensitive to inaccurate measurements? In other words, which will have a larger error e? Does this agree with the trend you saw in Part (b)? EECS 16A, Spring 2018, Midterm 1 15

Extra page for scratchwork. Work on this page will NOT be graded. EECS 16A, Spring 2018, Midterm 1 16

Doodle page! Draw us something if you want or give us suggestions, compliments, or complaints. You can also use this page to report anything suspicious that you might have noticed. EECS 16A, Spring 2018, Midterm 1 17

EECS 16A Spring 2018 Designing Information Devices and Systems I Midterm 1 Instructions Read the following instructions before the exam. You have 120 minutes for the exam. There are 10 problems of varying numbers of points. The problems are of varying difficulty, so pace yourself accordingly and avoid spending too much time on any one question until you have gotten all of the other points you can. Partial credit will be given for substantial progress on each problem. The exam is printed double-sided. Do not forget the problems on the back sides of the pages! There are 18 pages on the exam, so there should be 9 sheets of paper in the exam. Notify a proctor immediately if a page is missing. Do not tear out or remove any of the pages. Do not remove the exam from the exam room. Write your student ID on each page before time is called. If a page is found without a student ID, we are not responsible for identifying the student who wrote that page. You may consult ONE handwritten 8.5 11 note sheet (front and back). No phones, calculators, tablets, computers, other electronic devices, or scratch paper are allowed. No collaboration is allowed, and do not attempt to cheat in any way. Cheating will not be tolerated. Please write your answers legibly in the spaces provided on the exam; we will not grade outside a problem s designated space unless you specifically tell us where to find your work. In general, show all of your work in order to receive full credit. If you need to use the restrooms during the exam, bring your student ID card, your phone, and your exam to a proctor. You can collect them once you return from the restrooms. Our advice to you: if you can t solve the problem, state and solve a simpler one that captures at least some of its essence. You might get some partial credit, and more importantly, you will perhaps find yourself on a path to the solution. Good luck! EECS 16A, Spring 2018, Midterm 1 Instructions 1