EE-Learning
Mod-01 Lec-10 Markov Chain
Catogry:
Computing
Subject:
Computer Science
Course:
Performance Evaluation Of Computer Systems
Lecture List
Mod-01 Lec-41 PetriNets-II
Mod-01 Lec-39 PetriNets-I
Mod-01 Lec-38 Discrete-event simulations-III
Mod-01 Lec-37 Programming aspects of discrete-event simulations-II
Mod-01 Lec-36 Programming aspects of discrete-event simulations-I
Mod-01 Lec-35 2k r factorial design and 2k-p fractional factorial design
Mod-01 Lec-34 2k factorial design
Mod-01 Lec-33 Confidence interval for propotions and introduction to experimental design
Mod-01 Lec-32 Balanced Job Bounds
Mod-01 Lec-31 Hierarchical decomposition
Mod-01 Lec-30 Load-dependent service centers
Mod-01 Lec-29 Convolution algorithm-I
Mod-01 Lec-28 Convolution algorithm-I
Mod-01 Lec-27 Approximate MVA
Mod-01 Lec-26 Open and closed queuing networks
Mod-01 Lec-25 Operational laws-II
Mod-01 Lec-24 Operational laws-I
Mod-01 Lec-23 Simulations-III
Mod-01 Lec-22 Simulations-II
Mod-01 Lec-21 Simulations-I
Mod-01 Lec-20 Slotted Aloha Markov model
Mod-01 Lec-19 Queuing networks-I
Mod-01 Lec-18 Queuing theory-VI
Mod-01 Lec-17 Queuing theory-V
Mod-01 Lec-16 Queuing theory-IV
Mod-01 Lec-15 Queuing theory-IV
Mod-01 Lec-14 Queuing theory-III
Mod-01 Lec-13 Queuing theory — II
Mod-01 Lec-12b Queuing theory — I (Continued)
Mod-01 Lec-12 Continuous time Markov chain and queuing theory-I
Mod-01 Lec-11 Slotted Aloha protocol model and discrete-time birth death process
Mod-01 Lec-10 Markov Chain
Mod-01 Lec-09 Stochastic process
Mod-01 Lec-08 Probability distributions-III
Mod-01 Lec-07 Probability distributions-II
Mod-01 Lec-06 Probability distributions-I
Mod-01 Lec-05 Random Variables and probability distributions
Mod-01 Lec-04 Case study: Selection of techniques and metrics
Mod-01 Lec-03 Selection of techniques and metrics
Mod-01 Lec-02 How to avoid common mistakes
Mod-01 Lec-01 Introduction to performance evaluation of computer systems