7 Million Study Materials
From students who've taken these classes before
Personal attention for all your questions
Learn
93% of our members earn better grades
UCSD | EECS 153
Probability&Random Process
Professors
• Kim

11 sample documents related to EECS 153

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #21 Tuesday, May 3, 2011 Midterm Examination (Spring 2010) (Total: 120 points) There are 3 problems, each problem with 4 parts, each part worth 10 points. Your answer should be as clear and readable as possible. 1.

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #20 Tuesday, May 3, 2011 Midterm Examination (Spring 2008) (Total: 80 points) 1. First available teller (20 points). Consider a bank with two tellers. The service times for the tellers are independent exponentially

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #19 Tuesday, May 3, 2011 Midterm Examination (Fall 2008) (Total: 120 points) There are 3 problems, each problem with 4 parts, each part worth 10 points. Your answer should be as clear and readable as possible. In pa

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #37 Thursday, May 26, 2011 Final Examination (Spring 2010) (Total: 180 points) Your answer should be as clear, readable (and short) as possible. 1. Polya\'s urn revisited (40 points). Suppose we have an urn containin

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #36 Thursday, May 26, 2011 Final Examination (Spring 2008) 1. Coin with random bias (20 points). You are given a coin but are not told what its bias (probability of heads) is. You are told instead that the bias is t

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #35 Thursday, May 26, 2011 Final Examination (Fall 2008) 1. Order statistics. Let X1 , X2 , X3 be independent and uniformly drawn from the interval [0, 1]. Let Y1 be the smallest of X1 , X2 , X3 , let Y2 be the medi

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Homework Set #7 Due: Thursday, June 2, 2011 Handout #33 Thursday, May 26, 2011 1. Symmetric random walk. Let Xn be a random walk defined by X0 = 0, n Xn = i=1 Zi , 1 where Z1 , Z2 , . . . are i.i.d. with Pcfw_Z1 = -1 = Pcfw

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Homework Set #6 Due: Thursday, May 26, 2011 Handout #26 Thursday, May 19, 2011 1. Covariance matrices. Which of the following matrices can be a covariance matrix? Justify your answer either by constructing a random vector X

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #18 Thursday, April 28, 2011 Homework Set #5 Due: Thursday, May 5, 2011 1. Neural net. Let Y = X + Z, where the signal X U[-1, 1] and noise Z N (0, 1) are independent. (a) Find the function g(y) that minimizes MSE =

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #15 Thursday, April 21, 2011 Homework Set #4 Due: Thursday, April 28, 2010 1. Two independent uniform random variables. Let X and Y be independently and uniformly drawn from the interval [0, 1]. (a) Find the pdf of

• UCSD EECS 153
UCSD ECE153 Prof. Young-Han Kim Handout #12 Thursday, April 14, 2011 Homework Set #3 Due: Thursday, April 21, 2011 1. Time until the n-th arrival. Let the random variable N(t) be the number of packets arriving during time (0, t]. Suppose N(t) is Poisson w