Unit III: Random Processes

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This unit provides an introduction to some simple classes of discrete random processes. This includes the Bernoulli and Poisson processes that are used to model random arrivals and for which we characterize various associated random variables of interest and study several general properties. It also includes Markov chains, which describe dynamical systems that evolve probabilistically over a finite state space. We present the general structure of Markov models and study both their long-term and transient behavior.

Lecture_13.jpg Lecture 13: Bernoulli Process

Lecture_14.jpg Lecture 14: Poisson Process - I

Lecture_15.jpg Lecture 15: Poisson Process - II

Lecture_16.jpg Lecture 16: Markov Chains - I

Lecture_17.jpg Lecture 17: Markov Chains - II

Lecture_18.jpg Lecture 18: Markov Chains - III


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