Advanced Random Processes (2011 Spring)

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Course Information

Course Advanced Random Processes (Lectures in English)
Department Electronics Engineering
Course Number G14670
Hours 3 hours (MW, 2:00~3:15PM)
Credits 3.0 credits
Instructor Prof. Hyunggon Park
Office Engineering A Bldg. 514
Tel. 3277-3896

Course Objectives

Introduction to probably, random variable, random processes and stochastic processes as applied to study of communication systems and signal processing. A tentative list of the covered topics is basic probability, random variable and processes, Gaussian random variable and process, Poisson process, Markov chains, Markov process, and optionally, renewal theory.

Texts and References

  • Texts
  1. Textbooks
    1. Robert G. Gallagher, Discrete Stochastic Processes, Kluwer Academic Publishers 2001, ISBN 978-0-79239-583-6
  1. References
    1. Hoel, Port and Stone, Introduction to Stochastic Process, Waveland 1987, ISBN 978-0-88133-267-4
    2. Cinlar, E., Introduction to Stochastic Processes, Engelwood Cliffs, N.J.: Prentice Hall, 1975. ISBN 978-0-13498-089-8

Course Structures and Teaching Methods


Course Requirements and Assignments

Students are required to do their homework and projects.

Evaluation and Grades

  1. Homework (15%)
  2. Midterm Exam (35%)
  3. Final Exam (50%)

Tentative Course Outline

A tentative list of the covered topics:

  • Review of basic probability (2 week)
  • Review of random variable and processes (2 weeks)
  • Gaussian random variable and process (1 week)
  • Poisson process (2 weeks)
  • Markov chains (3 weeks)
  • Markov Process I (2 weeks)
  • Markov Process II (2 weeks)
  • (Renewal theory)