Markov Processes for Stochastic Modeling

Author:   Oliver Ibe (University of Massachusetts, Lowell, USA)
Publisher:   Elsevier - Health Sciences Division
Edition:   2nd edition
ISBN:  

9780323282956


Pages:   516
Publication Date:   01 June 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Markov Processes for Stochastic Modeling


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Author:   Oliver Ibe (University of Massachusetts, Lowell, USA)
Publisher:   Elsevier - Health Sciences Division
Imprint:   Elsevier - Health Sciences Division
Edition:   2nd edition
Dimensions:   Width: 15.20cm , Height: 2.60cm , Length: 22.90cm
Weight:   0.450kg
ISBN:  

9780323282956


ISBN 10:   0323282954
Pages:   516
Publication Date:   01 June 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Basic Concepts Chapter 2: Introduction to Markov Processes  Chapter 3: Discrete-Time Markov Chains Chapter 4: Continuous-Time Markov Chains  Chapter 5: Markovian Queueing Systems  Chapter 6: Markov Renewal Processes Chapter 7: Markovian Arrival Processes  Chapter 8: Random Walk Chapter 9: Brownian Motion and Diffusion Processes  Chapter 10: Controlled Markov  Processes Chapter 11: Hidden Markov Models Chapter 12: Markov Point Processes

Reviews

""Markov processes are the most popular modeling tools for stochastic systems in many different fields, and Ibe compiles in a single volume many of the Markovian models used indifferent disciplines. The information could be useful to graduate students and researchers in any field that uses Markov processes, he says, but he was thinking particularly of those in traffic engineering, image analysis, bioinformatics, biostatistics, financial engineering, and computational biology."" --Reference and Research Book News, October 2013


Markov processes are the most popular modeling tools for stochastic systems in many different fields, and Ibe compiles in a single volume many of the Markovian models used indifferent disciplines. The information could be useful to graduate students and researchers in any field that uses Markov processes, he says, but he was thinking particularly of those in traffic engineering, image analysis, bioinformatics, biostatistics, financial engineering, and computational biology. --Reference and Research Book News, October 2013


"""Markov processes are the most popular modeling tools for stochastic systems in many different fields, and Ibe compiles in a single volume many of the Markovian models used indifferent disciplines. The information could be useful to graduate students and researchers in any field that uses Markov processes, he says, but he was thinking particularly of those in traffic engineering, image analysis, bioinformatics, biostatistics, financial engineering, and computational biology."" --Reference and Research Book News, October 2013"


Author Information

Dr Ibe has been teaching at U Mass since 2003. He also has more than 20 years of experience in the corporate world, most recently as Chief Technology Officer at Sineria Networks and Director of Network Architecture for Spike Broadband Corp.

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