Revision as of 16:11, 25 January 2014 by Chen558 (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)


ECE Ph.D. Qualifying Exam

Communication, Networking, Signal and Image Processing (CS)

Question 1: Probability and Random Processes

August 2012



Question

Part 1. 25 pts


 $ \color{blue}\text{State and prove the Chebyshev inequality for random variable} \mathbf{X}\text{ with mean}\mathbf{\mu}\text{ and variance } \mathbf{\sigma^2} \text{. In constructing your proof, keep in mind that} \mathbf{X} \text{ may be either a discrete or continuous random variable} $


Click here to view student answers and discussions

Part 2. 25 pts


 $ \color{blue} \text{Show that if a continuous-time Gaussian random process } \mathbf{X}(t) \text{ is wide-sense stationary, it is also strict-sense stationary.} $


Click here to view student answers and discussions

Back to ECE Qualifying Exams (QE) page

Alumni Liaison

Abstract algebra continues the conceptual developments of linear algebra, on an even grander scale.

Dr. Paul Garrett