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Stochastic Processes. Instructor: Dr. S. Dharmaraja, Department of Mathematics, IIT Delhi.
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Description
This course explains and exposits concepts of stochastic processes which they need for their experiments and research. It also covers theoretical concepts pertaining to handling various stochastic modeling. This course provides classification and properties of stochastic processes, stationary processes, discrete and continuous time Markov chains and simple Markovian queueing models. (from nptel.ac.in)
Course content
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- Lecture 01 – Introduction to Stochastic Processes Unlimited
- Lecture 02 – Introduction to Stochastic Processes (cont.) Unlimited
- Lecture 03 – Problems in Random Variables and Distributions Unlimited
- Lecture 04 – Problems in Sequences of Random Variables Unlimited
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- Lecture 05 – Definition, Classification and Examples Unlimited
- Lecture 06 – Simple Stochastic Processes Unlimited
- Lecture 07 – Stationary Processes Unlimited
- Lecture 08 – Autoregressive Processes Unlimited
- Lecture 16 – Definition, Kolmogorov Differential Equations and Infinitesimal Generator Matrix Unlimited
- Lecture 17 – Limiting and Stationary Distributions, Birth Death Processes Unlimited
- Lecture 18 – Poisson Processes Unlimited
- Lecture 19 – M/M/1 Queueing Model Unlimited
- Lecture 20 – Simple Markovian Queuing Models Unlimited
- Lecture 21 – Queuing Networks Unlimited
- Lecture 22 – Communication Systems Unlimited
- Lecture 23 – Stochastic Petri Nets Unlimited
- Lecture 26 – Definition and Properties Unlimited
- Lecture 27 – Processes Derived from Brownian Motion Unlimited
- Lecture 28 – Stochastic Differential Equations Unlimited
- Lecture 29 – Ito Integrals Unlimited
- Lecture 30 – Ito Formula and its Variants Unlimited
- Lecture 31 – Some Important Stochastic Differential Equations and their Solutions Unlimited
- Lecture 38 – Galton-Watson Process Unlimited
- Lecture 39 – Markovian Branching Process Unlimited
Instructor
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