ECE 534 Problem Set 2: Convergence of Sequences of Random Variables, Assignments of Electrical and Electronics Engineering

A problem set for ece 534: random processes, fall 2007. It includes assigned reading and a list of problems to be handed in, with instructions for problem 2.11 to use the central limit theorem and chernoff bound, and for problem 2.13(c) to indicate if there is not enough information to determine certain forms of convergence.

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Pre 2010

Uploaded on 03/11/2009

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ECE 534 RANDOM PROCESSES FALL 2007
PROBLEM SET 2 Due Wednesday, September 19th
Please visit the course website: http://courses.ece.uiuc.edu/ece534/fall07/index.html
2.Convergence of a Sequence of Random Variables
Assigned reading: Chapter 2 and Sections 8.1-8.3 of the course notes.
Problems to be handed in:
2.3, 2.5, 2.7, 2.9, 2.11, 2.13, 2.15, 2.19, 2.21, and 2.23 from the course notes.
For problem 2.11, estimate the required probability using the central limit theorem and the
Chernoff bound, and compare these results to the exact probability which can be computed
numerically.
In problem 2.13(c), if there is not enough information to answer whether certain forms of
convergence take place or not, you can say so.
For problem 2.21, it may be useful to know that the characteristic function ΦX(u) of a random
variable Xis continuous in u. Thus, if a function is not continuous in u, then it cannot be a
characteristic function.
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ECE 534 RANDOM PROCESSES FALL 2007

PROBLEM SET 2 Due Wednesday, September 19th

Please visit the course website: http://courses.ece.uiuc.edu/ece534/fall07/index.html

2.Convergence of a Sequence of Random Variables

Assigned reading: Chapter 2 and Sections 8.1-8.3 of the course notes.

Problems to be handed in:

2.3, 2.5, 2.7, 2.9, 2.11, 2.13, 2.15, 2.19, 2.21, and 2.23 from the course notes.

  • For problem 2.11, estimate the required probability using the central limit theorem and the Chernoff bound, and compare these results to the exact probability which can be computed numerically.
  • In problem 2.13(c), if there is not enough information to answer whether certain forms of convergence take place or not, you can say so.
  • For problem 2.21, it may be useful to know that the characteristic function ΦX (u) of a random variable X is continuous in u. Thus, if a function is not continuous in u, then it cannot be a characteristic function.