## E2 202 : Random Processes, Fall 2018## Lectures02 Aug 2018: Lecture-01 Preliminaries 07 Aug 2018: Lecture-02 Probability laws 09 Aug 2018: Lecture-03 Bayes’ Theorem and Independence of events
## Homeworks17 Aug 2018: Homework 1
## Tutorials
04 Aug 2018: Sample space, sigma algebra, example constructions of sigma algebras, “infinitely often” and “all but finitely many” events (Notes and exercises) 11 Aug 2018: Probability measure, continuity of probability, independence (Notes and exercises)
## Tests## Grading PolicyMid Term 1: 15% ## Course Syllabus**Probability Theory:**axioms, continuity of probability, independence, conditional probability.**Random variables:**distribution, transformation, expectation, moment generating function, characteristic function**Random vectors:**joint distribution, conditional distribution, expectation, Gaussian random vectors.**Convergence of random sequences:**Borel-Cantelli Lemma, laws of large numbers, central limit theorem, Chernoff bound.**Discrete time random processes:**ergodicity, strong ergodic theorem, definition, stationarity, correlation functions in linear systems, power spectral density.**Structured random processes:**Bernoulli processes, independent increment processes, discrete time Markov chains, recurrence analysis, Foster's theorem, reversible Markov chains, the Poisson process.
## Course DescriptionBasic 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. ## Slack Information## SlackStudents can signup for course slack using their iisc.ac.in email at Slack signup. ## InstructorsUtpal Mukherji Parimal Parag ## Time and LocationClassroom: ECE 1.08, Main ECE Building. ## Teaching AssistantsKarthik P N Prathamesh Mayekar ## TextbooksProbability and Random Processes, Geoffrey Grimmett and David Stirzaker, 3rd edition, 2001. Discrete Event Stochastic Processes, Anurag Kumar, Department of Electrical Communication Engineering, Indian Institute of Science Random Processes for Engineers, Bruce Hajek, 2014. Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklis, 2nd edition, 2008. A First Course in Probability, Sheldon M. Ross, 2013. Probability Essentials, Jean Jacod & Philip Protter, Springer, 2004. Probability, Random processes, and Statistical Analysis: Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance, Kobayashi, Hisashi, Brian L. Mark, and William Turin, Cambridge University Press, 2011. |