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Unformatted text preview: ECE4110 General Information Fall 2009 Cornell University T.L.Fine CATALOG DESCRIPTION: ECE 4110 Random Signals in Communications and Signal Processing Fall. 4 credits. Prerequisite: ECE 2200 and ECE 3100 or equivalent. Introduction to models for random signals in discrete and continuous time; Markov chains, Poisson process, queuing processes, power spectral densities, Gaussian random process. Response of linear systems to random signals. Elements of estimation and inference as they arise in communications and digital signal processing systems. STAFF: Instructor—Terrence L. Fine, 221 Phillips, email: [email protected] Administrative Assistant—Sue Bulkley in 314 Rhodes, [email protected] CLASS and OFFICE HOURS: Class meets on Tuesdays and Thursdays from 2:55pm to 4:10pm in Phillips 403. Professor Fine will usually hold office hours on Wednesdays from 4pm to 5pm in RH 312. BLACKBOARD WEBSITE: Blackboard provides a site for ECE4110 to which course materials will be posted—homeworks and solutions to homeworks, exam solutions, and occa- sional supplementary material and notes. Please enroll ASAP in Blackboard for ECE4110. Enrolling in the Blackboard course site is unrelated to enrolling in ECE4110 for credit. If you need information about how to use Blackboard, please go to http://atc.cit.cornell.edu/blackboard In the event of spread of H1N1 infection, this Blackboard site will enable us to remain in communication. 1 COURSE GOALS: An introduction to the concepts, mathematical methods, and frequently en- countered models that are commonly employed to describe random phenom- ena that have temporal and/or spatial variation. Key examples include ran- dom signals varying in time that may either be discrete or continuous and...
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This note was uploaded on 10/20/2009 for the course ECE 4110 at Cornell University (Engineering School).
- Signal Processing