Media Storage Type : 32 GB USB Stick
NPTEL Subject Matter Expert : Dr. S. Dharmaraja
NPTEL Co-ordinating Institute : IIT Delhi
NPTEL Lecture Count : 39
NPTEL Course Size : 23 GB
NPTEL PDF Text Transcription : Available and Included
NPTEL Subtitle Transcription : Available and Included (SRT)
Lecture Titles:
Lecture 1 - Introduction to Stochastic Processes
Lecture 2 - Introduction to Stochastic Processes (Continued.)
Lecture 3 - Problems in Random Variables and Distributions
Lecture 4 - Problems in Sequences of Random Variables
Lecture 5 - Definition, Classification and Examples
Lecture 6 - Simple Stochastic Processes
Lecture 7 - Stationary Processes
Lecture 8 - Autoregressive Processes
Lecture 9 - Introduction, Definition and Transition Probability Matrix
Lecture 10 - Chapman-Kolmogrov Equations
Lecture 11 - Classification of States and Limiting Distributions
Lecture 12 - Limiting and Stationary Distributions
Lecture 13 - Limiting Distributions, Ergodicity and Stationary Distributions
Lecture 14 - Time Reversible Markov Chain, Application of Irreducible Markov Chain in Queueing Models
Lecture 15 - Reducible Markov Chains
Lecture 16 - Definition, Kolmogrov Differential Equations and Infinitesimal Generator Matrix
Lecture 17 - Limiting and Stationary Distributions, Birth Death Processes
Lecture 18 - Poisson Processes
Lecture 19 - M/M/1 Queueing Model
Lecture 20 - Simple Markovian Queueing Models
Lecture 21 - Queueing Networks
Lecture 22 - Communication Systems
Lecture 23 - Stochastic Petri Nets
Lecture 24 - Conditional Expectation and Filtration
Lecture 25 - Definition and Simple Examples
Lecture 26 - Definition and Properties
Lecture 27 - Processes Derived from Brownian Motion
Lecture 28 - Stochastic Differential Equations
Lecture 29 - Ito Integrals
Lecture 30 - Ito Formula and its Variants
Lecture 31 - Some Important SDE`s and Their Solutions
Lecture 32 - Renewal Function and Renewal Equation
Lecture 33 - Generalized Renewal Processes and Renewal Limit Theorems
Lecture 34 - Markov Renewal and Markov Regenerative Processes
Lecture 35 - Non Markovian Queues
Lecture 36 - Non Markovian Queues Cont,,
Lecture 37 - Application of Markov Regenerative Processes
Lecture 38 - Galton-Watson Process
Lecture 39 - Markovian Branching Process