Mod-01 Lec-29 Convolution algorithm-I

Course Lectures

• Mod-01 Lec-01 Introduction to performance evaluation of computer systems

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• Mod-01 Lec-02 How to avoid common mistakes

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• Mod-01 Lec-03 Selection of techniques and metrics

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• Mod-01 Lec-04 Case study: Selection of techniques and metrics

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• Mod-01 Lec-05 Random Variables and probability distributions

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• Mod-01 Lec-06 Probability distributions-I

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• Mod-01 Lec-07 Probability distributions-II

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• Mod-01 Lec-08 Probability distributions-III

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• Mod-01 Lec-09 Stochastic process

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• Mod-01 Lec-10 Markov Chain

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• Mod-01 Lec-11 Slotted Aloha protocol model and discrete-time birth death process

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• Mod-01 Lec-12 Continuous time Markov chain and queuing theory-I

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• Mod-01 Lec-12b Queuing theory -- I (Continued)

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• Mod-01 Lec-13 Queuing theory -- II

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• Mod-01 Lec-14 Queuing theory-III

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• Mod-01 Lec-15 Queuing theory-IV

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• Mod-01 Lec-16 Queuing theory-IV

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• Mod-01 Lec-17 Queuing theory-V

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• Mod-01 Lec-18 Queuing theory-VI

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• Mod-01 Lec-19 Queuing networks-I

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• Mod-01 Lec-20 Slotted Aloha Markov model

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• Mod-01 Lec-21 Simulations-I

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• Mod-01 Lec-22 Simulations-II

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• Mod-01 Lec-23 Simulations-III

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• Mod-01 Lec-24 Operational laws-I

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• Mod-01 Lec-25 Operational laws-II

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• Mod-01 Lec-26 Open and closed queuing networks

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• Mod-01 Lec-27 Approximate MVA

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• Mod-01 Lec-28 Convolution algorithm-I

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• Mod-01 Lec-29 Convolution algorithm-I

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• Mod-01 Lec-30 Load-dependent service centers

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• Mod-01 Lec-31 Hierarchical decomposition

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• Mod-01 Lec-32 Balanced Job Bounds

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• Mod-01 Lec-33 Confidence interval for propotions and introduction to experimental design

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• Mod-01 Lec-34 2k factorial design

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• Mod-01 Lec-35 2k r factorial design and 2k-p fractional factorial design

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• Mod-01 Lec-36 Programming aspects of discrete-event simulations-I

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• Mod-01 Lec-37 Programming aspects of discrete-event simulations-II

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• Mod-01 Lec-38 Discrete-event simulations-III

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• Mod-01 Lec-39 PetriNets-I

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• Mod-01 Lec-40 PetriNets-II

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• Mod-01 Lec-41 PetriNets-III

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