Advanced Random Processes (2021 Spring)

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Course Information

Course Advanced Random Processes (Lectures in English)
Department Electronics Engineering
Course Number G14670
Hours 3 hours (W, 15:30-18:15)
Credits 3.0 credits
Instructor Prof. Hyunggon Park
Office Engineering B Bldg. 155
Tel. 3277-3896

Course Objectives

Introduction to probability, 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 a 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, Englewood 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)