E2 202: Random Processes (3:0)
August 2026
Instructor
Teaching Assistants
Sowmya S
Ram Rathan KR
Tithi Chethan Mahajani
Dwaipayan Halder
Yash Pandey
Lecture Hours
Lectures: Tuesdays and Thursdays, 14:00 - 15:30 hrs
Location: MP20 (Microelectronics and Photonics Building of the ECE Department)
First class: Tuesday 04 August 2026, 14:00 - 15:30 hrs
Lecture Plan
Office Hours and Tutorial Sessions
Tutorials: Saturdays 10:00 - 11:30 hrs, handled by TAs
Location: MP20
Problem Sets
Examinations
Practice test: Thursday 25 September 2026, 18:00 - 19:30 hrs
Mid-term 1: Saturday 05 September 2026, 10:00 - 11:30 hrs
Mid-term 2: Saturday 10 October 2026, 10:00 - 11:30 hrs
Mid-term 3: Saturday 07 November 2026, 10:00 - 11:30 hrs
Final: November 2026, as per SCC announcement
Course syllabus
The axioms of probability theory, continuity of probability, independence and conditional probability. Random variables and their distribution, functions of a random variable, expectation. Jointly distributed random variables, conditional distribution and expectation, Gaussian random vectors. Convergence of sequences of random variables, Borel-Cantelli Lemma, laws of large numbers and central limit theorem for sequences of independent random variables, Markov inequality. Definition of a random process, stationarity. Discrete time Markov chains, recurrence analysis, Foster's theorem. The Poisson process.
Course Grade
- 50% From three mid-term examinations
- 50% Final examination
- Home work assignments will be given on a periodic basis.
Reference Text
Supplementary Reading
- P. Bremaud, Introduction to Probabilistic Modeling, Springer-Verlag, 1988
- M. Loève, Probability Theory I, 4th edition, Springer-Verlag, 1977
- G. R. Grimmett and D. R. Stirzaker, Probability and Random Processes, Oxford University Press, 2020
- B. Hajek, Random Processes for Engineers, Cambridge University Press, 2015