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Random Processes Course at University of Illinois Urbana-Champaign, Spring 2012 (ECE 534) , Lecture notes of Electrical and Electronics Engineering

Information about the graduate-level course ece 534: random processes offered by the department of electrical and computer engineering at the university of illinois urbana-champaign in spring 2012. The course, taught by professor olgica milenkovic and teaching assistant figen, covers basic concepts of random processes and their applications in communications, signal processing, control systems engineering, and computer science. Students are expected to have a background in probability theory, sets, sequences, convergence, linear algebra, linear systems, and fourier transforms. The course includes two midterm exams, weekly homework, and a final exam. The required course notes are b. Hajek's an exploration of random processes for engineers, and additional references are provided. The document also includes the syllabus, contact information, office hours, and a detailed list of topics covered.

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2011/2012

Uploaded on 04/10/2012

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Download Random Processes Course at University of Illinois Urbana-Champaign, Spring 2012 (ECE 534) and more Lecture notes Electrical and Electronics Engineering in PDF only on Docsity! Department of Electrical and Computer Engineering ECE 534: RANDOM PROCESSES, SPRING 2012 This is a graduate-level course on random (stochastic) processes, which builds on a first-level (undergraduate) course on probability theory, such as ECE 313. It covers the basic concepts of random processes at a fairly rigorous level, and also discusses applications to communications, signal processing, control systems engineering, and computer science. To follow the course, in addition to basic notions of probability theory, students are expected to have some familiarity with the basic notions of sets, sequences, convergence, linear algebra, linear systems, and Fourier transforms. Meeting times: Tuesdays and Thursdays, 2:00–3:20 p.m. in 253 MEB In addition: The TA, Figen, will lead recitation sessions on Wednesday, 4:00–5:00 p.m. in Room Everitt 170 to discuss problems and solutions from the course notes. MIDTERM EXAMS: Monday, 20th of February, 2012 (6pm) and Friday, 30th of March, 2012 (6pm). Instructor: Professor Olgica Milenkovic Teaching assistant: S. Figen Oktem Contact information: Milenkovic: 126 Coordinated Science Laboratory (Phone: 244-7358) milenkov at uiuc dot edu TA: oktem1 at illinois dot edu Office hours: Wednesdays: 11 a.m.–1 p.m. in 126 CSL (usually Milenkovic) Tuesdays: 4 p.m.–5 p.m. in 368 Everitt Lab (usually Figen) Required course notes: B. Hajek, An Exploration of Random Processes for Engineers. Available for download at http://www.ifp.illinois.edu/~hajek/Papers/randomprocesses.html and for sale in the ECE Store, Room 60 Everitt Laboratory. Additional References: • W. Feller, An Introduction to Probability Theory and Its Applications, Vol. I, II, Wiley, 1968. • R.G. Gallager, Discrete Stochastic Processes, Kluwer, 1996. • R. Durrett, Probability: Theory and Examples, Duxbury Press, 2004. • H. Stark and J. W. Woods, Probability and Random Processes, and Estimation Theory for Engineers, third edition, Prentice Hall, 2002. • W.B. Davenport, Jr. and W.L. Root, An Introduction to the Theory of Random Signals and Noise, McGraw Hill, 1987 edition. • E. Wong and B. Hajek, Stochastic Processes in Engineering Systems, Springer Verlag, 1985. • A. Papoulis, Probability, Random Variables and Stochastic Processes, 2nd edt., McGraw Hill, 1984. • E. Wong, Introduction to Random Processes, Springer Verlag, 1983. • B.D.O. Anderson and J.B. Moore, Optimal Filtering, Prentice Hall, 1979. • W. Rudin, Principles of Mathematical Analysis, 3rd Edition, McGraw-Hill, New York, 1976. • R.B. Ash, Basic Probability Theory, Academic Press, 1972. • L. Breiman, Probability, Addison-Wesley, 1968. • H. Cramer and M.R. Leadbetter, Stationary and Related Stochastic Processes, Wiley, 1967. • E. Parzen, Stochastic Processes, Holden Day, 1962. Additional references, free for download: • R. M. Gray, Probability, Random Proceses, and Ergodic Properties • R.M. Gray and L.D. Davisson, Introduction to Statistical Signal Processing Grading: The point weighting formula: • 10% Homework • 20% Exam 1 (TBA) • 20% Exam 2 (TBA) • 40% Final Exam (TBA) • 10% Two in-class tests that WILL NOT BE ANNOUNCED in advance. Running scores for ECE 534 will be maintained on the Illinois Compass system (blue stem password required). Collaboration on the homework is permitted, however each student must write and submit independent solutions. Homework is due within the first 5 minutes of the class period on the due date. No late homework will be accepted (unless an extension is granted in advance by the instructor). You may bring one sheet of notes to the first hour exam, two to the second hour exam, and three to the final exam. You may use both sides of the sheets, the sheets are to be standard US or European size with font size 10 or larger printing (or similar handwriting size). The examinations are closed book otherwise. Calculators, laptop computers, tables of integrals, etc. are not permitted.
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