Midterm Exam II for ECE534 - Spring 2006, Exams of Electrical and Electronics Engineering

The midterm exam questions for the ece534 course during the spring 2006 semester. The exam consists of five problems, covering topics such as markov processes, martingales, brownian motion, and gaussian random processes. Students are allowed one sheet of notes and must solve each problem within the given time frame. The problems involve finding expected times, proving inequalities, and calculating mean and autocorrelation functions.

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Pre 2010

Uploaded on 03/10/2009

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Midterm Exam II
ECE534 Spring 2006
There are a total of five problems April 12, 7:00-8:30 pm
You are allowed one sheet (two pages) of notes; no calculators. Each problem is worth 20 points
Please put your NAME here:
1. Consider an object performing a random walk on the vertices of a square. At each time step,
the object stays at the same vertex that it was at the previous time step with probability 1/3 or
it moves to one of the two adjacent vertices, each with probability 1/3.Let Xbe a discrete-time
random process such that Xndenotes the position of the object at time step n. Name the vertices
of the square A, B, C and D, such that Aand Care diagonally opposite vertices. Assume X0=A.
Let
Tj= min{n1 : Xn=j},
where jcan be either A, B, C or D, and let yj=E(Tj).Thus, yjis the expected time to reach
vertex j, starting from vertex A. Note that nis taken to be greater than or equal to 1 in the
definition of Tj.
(a) Is X a Markov process? Explain your answer.
(b) Find yA.(Hint: Let t1be the exp ected time to reach vertex Astarting from either vertex
Bor vertex Dand let t2be the expected time to reach Astarting from C. Find equations relating
yA, t1and t2.)
(c) Find yB, yCand yD.
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Midterm Exam II

ECE534 Spring 2006 There are a total of five problems April 12, 7:00-8:30 pm You are allowed one sheet (two pages) of notes; no calculators. Each problem is worth 20 points

Please put your NAME here:

  1. Consider an object performing a random walk on the vertices of a square. At each time step, the object stays at the same vertex that it was at the previous time step with probability 1/3 or it moves to one of the two adjacent vertices, each with probability 1/ 3. Let X be a discrete-time random process such that Xn denotes the position of the object at time step n. Name the vertices of the square A, B, C and D, such that A and C are diagonally opposite vertices. Assume X 0 = A. Let Tj = min{n ≥ 1 : Xn = j},

where j can be either A, B, C or D, and let yj = E(Tj ). Thus, yj is the expected time to reach vertex j, starting from vertex A. Note that n is taken to be greater than or equal to 1 in the definition of Tj. (a) Is X a Markov process? Explain your answer. (b) Find yA. (Hint: Let t 1 be the expected time to reach vertex A starting from either vertex B or vertex D and let t 2 be the expected time to reach A starting from C. Find equations relating yA, t 1 and t 2 .) (c) Find yB , yC and yD.

  1. Let X be a discrete-time martingale. Show that

E(X n^2 |Xn− 1 , Xn− 2 ,... , X 1 ) ≥ X n^2 − 1.

(Hint: (a − b)^2 ≥ 0 .)

  1. Let W be a Brownian motion. Define another random process Y as

Yt = Wt+D − Wt, t ≥ 0 ,

where D is some fixed positive number. (a) Find the mean and autocorrelation functions of Y. (b) Show that Y is a stationary process.

  1. Let X be a continuous-time, zero-mean Gaussian random process with autocorrelation function RX (t, s) = 2ts + t^2 s^2. (a) Does the random process Y defined by Yt = dX dtt exist in a mean square sense? Clearly explain your answer. (b) Find the mean and autocorrelation functions of Y. Do these functions completely specify all finite-order distributions of Yt? Clearly explain your answer.