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Random Processes: Filtering, Estimation, and Detection

Random Processes: Filtering, Estimation, and Detection

Random Processes: Filtering, Estimation, and Detection
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Random Processes: Filtering, Estimation, and Detection Hardback - 2002

by Lonnie C. Ludeman

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Description

IEEE, 2002. Hardcover. New. 1st edition. 632 pages. 9.25x6.25x1.25 inches.
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Details

  • Title Random Processes: Filtering, Estimation, and Detection
  • Author Lonnie C. Ludeman
  • Binding Hardback
  • Edition INTERNATIONAL ED
  • Condition New
  • Pages 632
  • Volumes 1
  • Language ENG
  • Publisher IEEE
  • Publication date 2002
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # x-0471259756
  • ISBN 9780471259756 / 0471259756
  • Weight 2.2 lbs (1.00 kg)
  • Dimensions 9.46 x 6.4 x 1.35 in (24.03 x 16.26 x 3.43 cm)
  • Category Technology & Industrial Arts
  • Library of Congress subjects Image processing, Stochastic processes
  • Library of Congress Catalogue Number 2003271410
  • Dewey Decimal Code 621.382
  • Quantity available 2

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Reader reviews for Random Processes: Filtering, Estimation, and Detection

From the publisher

An understanding of random processes is crucial to many engineering fields-including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vibrational theory and stress analysis in mechanical engineering. The filtering, estimation, and detection of random processes in noisy environments are critical tasks necessary in the analysis and design of new communications systems and useful signal processing algorithms. Random Processes: Filtering, Estimation, and Detection clearly explains the basics of probability and random processes and details modern detection and estimation theory to accomplish these tasks.
In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for classification purposes, and describe performance evaluation definitions and procedures for the resulting methods. The text covers four main, interrelated topics:

* Probability and characterizations of random variables and random processes
* Linear and nonlinear systems with random excitations
* Optimum estimation theory including both the Wiener and Kalman Filters
* Detection theory for both discrete and continuous time measurements

Lucid, thorough, and well-stocked with numerous examples and practice problems that emphasize the concepts discussed, Random Processes: Filtering, Estimation, and Detection is an understandable and useful text ideal as both a self-study guide for professionals in the field and as a core text for graduate students.

From the rear cover

An understanding of random processes is crucial to many engineering fields-including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vibrational theory and stress analysis in mechanical engineering. The filtering, estimation, and detection of random processes in noisy environments are critical tasks necessary in the analysis and design of new communications systems and useful signal processing algorithms. Random Processes: Filtering, Estimation, and Detection clearly explains the basics of probability and random processes and details modern detection and estimation theory to accomplish these tasks.

In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for classification purposes, and describe performance evaluation definitions and procedures for the resulting methods. The text covers four main, interrelated topics:

  • Probability and characterizations of random variables and random processes
  • Linear and nonlinear systems with random excitations
  • Optimum estimation theory including both the Wiener and Kalman Filters
  • Detection theory for both discrete and continuous time measurements
  • Lucid, thorough, and well-stocked with numerous examples and practice problems that emphasize the concepts discussed, Random Processes: Filtering, Estimation, and Detection is an understandable and useful text ideal as both a self-study guide for professionals in the field and as a core text for graduate students.

    About the author

    LONNIE C. LUDEMAN, PhD, received his doctorate from Arizona State University and is Professor Emeritus of electrical and computer engineering at New Mexico State University. In 1993, he was a Fulbright Scholar at the Aristotle University in Thessaloniki, Greece. He is the author of Fundamentals of Digital Signal Processing, which won Choice magazine's award for Outstanding Engineering Book of the Year.

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