Probability, Random Processes, and Statistical Analysis
eBook - PDF

Probability, Random Processes, and Statistical Analysis

Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Probability, Random Processes, and Statistical Analysis

Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance

About this book

Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.

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Yes, you can access Probability, Random Processes, and Statistical Analysis by Hisashi Kobayashi,Brian L. Mark,William Turin in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Signals & Signal Processing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Probability, Random Processes, and Statistical Analysis
  3. Title
  4. Copyright
  5. Contents
  6. Abbreviations and Acronyms
  7. Preface
  8. Acknowledgments
  9. 1 Introduction
  10. Part I Probability, random variables, and statistics
  11. Part II Transform methods, bounds, and limits
  12. Part III Random processes
  13. Part IV Statistical inference
  14. Part V Applications and advanced topics