E2 202o, Fall 2025
Random Processes
Lectures
- 05 Aug 2025: Lecture-01 Sets
- 07 Aug 2025: Lecture-02 Functions
<!– - 12 Aug 2025: Lecture-03 Sample and event space
- 14 Aug 2025: Lecture-04 Probability function
- 19 Aug 2025: Lecture-03 Independence of events
- 21 Aug 2025: Lecture-04 Random variables
- 26 Aug 2025: Lecture-05 Random vectors
- 28 Aug 2025: Lecture-06 Transformations of random vectors
- 02 Sep 2025: Lecture-07 Random processes
- 04 Sep 2025: Lecture-08 Expectation
- 09 Sep 2025: Lecture-09 Moments and L^p space
- 11 Sep 2025: Lecture-10 Correlation
- 16 Sep 2025: Lecture-11 Generating functions
- 18 Sep 2025: Lecture-12 Conditional expectation
- 23 Sep 2025: Lecture-13 Properties of conditional expectation
- 25 Sep 2025: Lecture-14 Almost sure convergence
- 30 Sep 2025: Lecture-15 $L^p$ convergence
- 02 Oct 2025: Lecture-16 Weak convergence
- 07 Oct 2025: Lecture-17 Tractable Random Processes
- 09 Oct 2025: Lecture-18 Stopping Times
- 14 Oct 2025: Lecture-19 Markov Chains
- 16 Oct 2025: Lecture-20 DTMC: Strong Markov Property
- 21 Oct 2025: Lecture-21 DTMC: Transient and recurrent states
- 23 Oct 2025: Lecture-22 DTMC: Communicating classes
- 28 Oct 2025: Lecture-23 DTMC: Invariant Distribution
- 30 Oct 2025: Lecture-24 Poisson point processes
- 04 Nov 2025: Lecture-25 Poisson point processes: Conditional distribution
- 06 Nov 2025: Lecture-26 Poisson point processes: Properties
- 11 Nov 2025: Lecture-27 Poisson processes on half-line
- 13 Nov 2025: Lecture-28 Poisson Processes: Compound
–>
Homework
- 04 Aug 2025: Homework-01
- 18 Aug 2025: Homework-02
- 01 Sep 2025: Homework-03
- 15 Sep 2025: Homework-04
- 29 Sep 2025: Homework-05
- 13 Oct 2025: Homework-06
- 27 Oct 2025: Homework-07
- 10 Nov 2025: Homework-08
Tutorials
Homework discussions and Quizzes Saturday 02:00 pm - 03:30 pm
- 08 Aug 2025: Tutorial-01 Cardinality. Probability space. Limits of sets. Continuity of probability.
- 15 Aug 2025: Tutorial-02 Law of total probability. Independence of events. Conditional probability. Random variables.
- 22 Aug 2025: Tutorial-03 Random vectors. Transformation of random variables and random vectors.
- 29 Aug 2025: Tutorial-04 Random Processes. Expectation.
- 05 Sep 2025: Tutorial-05 Moments. Correlation. $L^p$ space. Inequalities.
- 12 Sep 2025: Tutorial-06 Generating functions. Conditional expectation.
- 19 Sep 2025: Tutorial-07 Almost sure convergence. Convergence in probability. Borel-Cantelli lemma.
- 24 Sep 2025: Tutorial-08 $L^p$ Convergence. Convergence in distribution. Problems on convergence of random variables.
- 26 Sep 2025: Tutorial-09 Law of large numbers. Central Limit theorem.
- 03 Oct 2025: Tutorial-10 Tractable random processes. Stopping times.
- 10 Oct 2025: Tutorial-11 Introduction to discrete time Markov chains.
- 17 Oct 2025: Tutorial-12 DTMC: Recurrent and transient states.
- 24 Oct 2025: Tutorial-13 DTMC: Communicating classes. Invariant distribution.
- 31 Oct 2025: Tutorial-14 Introduction to Poisson processes
- 07 Nov 2025: Tutorial-15 Thinning and superposition of Poisson processes
Tests
Quizzes: Saturday 03:00 pm - 03:30 pm
Mid-terms: Saturday 02:00 pm - 03:30 pm
Final: Wednesday 08:00 am - 12:00 noon
- 20 Aug 2025: Quiz-01
- 03 Sep 2025: Quiz-02
- 17 Sep 2025: Mid-term-01
- 01 Oct 2025: Quiz-03
- 15 Oct 2025: Quiz-04
- 29 Oct 2025: Mid-term-02
- 12 Nov 2025: Quiz-05
- 26 Nov 2025: Quiz-06
- 07 Dec 2025: Final
Grading Policy
Quizzes: 30
Mid Term: 30
Final: 40
Class participation is based on attendance and class interaction in lectures, tutorials, and homework discussions.
Course Syllabus
- Mathematical Preliminaries:
- Sets, Functions, Cardinality
- Probability Theory:
- axioms, continuity of probability, independence, conditional probability
- Random variables:
- distribution, transformation, expectation, conditional expectation, moment generating function, characteristic function
- Random vectors:
- joint distribution, conditional distribution, expectation, Gaussian random vectors.
- Convergence of random sequences:
- Borel-Cantelli Lemma, almost sure convergence, convergence in probability, convergence in $L^p$, weak convergence, laws of large numbers, central limit theorem, $L^1$ convergence theorems
- Discrete time random processes:
-
ergodicity, strong ergodic theorem,definition, stationarity, correlation functions in linear systems,power spectral density.
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- Structured random processes:
- Bernoulli processes, independent increment processes, discrete time Markov chains, recurrence analysis,
Foster’s theorem, reversible Markov chains,the Poisson process.
- Bernoulli processes, independent increment processes, discrete time Markov chains, recurrence analysis,
Course Description
Basic mathematical modeling is at the heart of engineering. In both electrical and computer engineering, uncertainty can be modeled by appropriate probabilistic objects. This foundational course will introduce students to basics of probability theory, random variables, and random sequences.
Teams Information
We will use Microsoft Teams for all the course related communication.
Please do not send any email regarding the course.
Students can signup for Microsoft Teams Random-Processes-2025 using their iisc.ac.in email.
Instructor
Parimal Parag
Office: EC 2.17
Hours: By appointment.
Time and Location
Hours: Tue/Thu 04:00 pm - 03:30pm.
Tutorial: Sat 02:00 pm - 03:30 pm.
Quizzes: Sat 03:00 pm - 03:30 pm.
Mid-term: Sat 02:00 pm - 03:30 pm.
Teaching Assistants
Aniket Mukherjee
Office: ESE 316
Hours: By appointment.
Moonmoon Mohanty
Office: EC 2.16
Hours: By appointment.
Nomula Taraka Sada Siva Srinivas
Office: EC 2.16
Hours: By appointment.
Venkatesan D
Office: EC 2.16
Hours: By appointment.
Textbooks
Probability and Random Processes, Geoffrey Grimmett and David Stirzaker, 3rd edition, 2001.
Probability and Random Processes: With Applications to Signal Processing and Communications, Scott L. Miller and Donald G. Childers, 2nd Edition, 2012.
Random Processes for Engineers, Bruce Hajek, 2014.
Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklis, 2nd edition, 2008.
Discrete Event Stochastic Processes, Anurag Kumar.