Stochastic Methods and Their Applications to Communications: Stochastic Differential Equations Approach / Edition 1

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Stochastic Methods & their Applications to Communications presents a valuable approach to the modelling, synthesis and numerical simulation of random processes with applications in communications and related fields. The authors provide a detailed account of random processes from an engineering point of view and illustrate the concepts with examples taken from the communications area. The discussions mainly focus on the analysis and synthesis of Markov models of random processes as applied to modelling such phenomena as interference and fading in communications. Encompassing both theory and practice, this original text provides a unified approach to the analysis and generation of continuous, impulsive and mixed random processes based on the Fokker-Planck equation for Markov processes.

  • Presents the cumulated analysis of Markov processes
  • Offers a SDE (Stochastic Differential Equations) approach to the generation of random processes with specified characteristics
  • Includes the modelling of communication channels and interfer ences using SDE
  • Features new results and techniques for the of solution of the generalized Fokker-Planck equation

Essential reading for researchers, engineers, and graduate and upper year undergraduate students in the field of communications, signal processing, control, physics and other areas of science, this reference will have wide ranging appeal.

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Editorial Reviews

From the Publisher
"The last chapter is an excellent exposition of applied models for the physical layer of communication systems" (The IEE Communications Engineer, February/March 2005)

"The book has brought together a wealth of material and techniques" (Zentralblatt MATH Volume 1081)

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Product Details

  • ISBN-13: 9780470847411
  • Publisher: Wiley
  • Publication date: 9/15/2004
  • Edition number: 1
  • Pages: 446
  • Product dimensions: 6.97 (w) x 9.96 (h) x 1.22 (d)

Table of Contents

1. Introduction.

2. Random Variables and Their Description.

3. Random Processes.

4. Advanced Topics in Random Processes.

5. Markov Processes and Their Description.

6. Markov Processes with Random Structures.

7. Synthesis of Stochastic Differential Equations.

8. Applications.


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