Homework Assignments:
Problem set 1 ...solutions
Problem set 2 ...solutions
Problem set 3 ...solutions
Problem set 4 ...solutions
Problem set 5 ...solutions
Problem set 6 ...solutions
Problem set 7 ...solutions

Quiz ...solutions
Exam 1 ...solutions
Exam 2 ...solutions
Final ...solutions

Syllabus

This is a graduate-level course on random (stochastic) processes, which builds on a first-level (undergraduate) course on probability theory, such as ECE 413 . It covers the basic concepts of random processes at a fairly rigorous level, and also discusses applications to communications, signal processing and control systems engineering. 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: 10-11:30 a.m. MW, Room 165 Everitt Lab

Instructor: Professor Bruce Hajek
Teaching assistants: Karen Guan and Hongxia Shen

Contact information:
Hajek: 105 Coordinated Science Laboratory (Phone: 333-3605) b-hajek at you eye you see dot edu
TAs : {kguan, hshen1} at you eye you see dot edu

Office hours:
Tuesdays 10-11 a.m. (TA) and 4-5 p.m. (instructor) in Room 365 Everitt Lab
Fridays 10-11 a.m. (recitation session by TA) in Room 165 Everitt Lab (usual classroom).

Required course notes: B. Hajek, An Exploration of Random Processes for Engineers.
Available for download at http://comm.csl.uiuc.edu/~hajek/Papers/randomprocesses.html
and also available for ($20.20 with tax) at the TIS Copy Shop, on Sixth Street a half block south of Green Street.

References reserved in Grainger Engineering Library:

• R.G. Gallager, Discrete Stochastic Processes, Kluwer, 1996.
• 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.