Central Library

Random processes : (Record no. 73971)

000 -LEADER
fixed length control field 05990nam a2201117 i 4500
001 - CONTROL NUMBER
control field 5271182
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220712205711.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151221s2003 njua ob 001 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780470547199
-- electronic
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- print
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- electronic
082 04 - CLASSIFICATION NUMBER
Call Number 621.38223
100 1# - AUTHOR NAME
Author Ludeman, Lonnie C.,
245 10 - TITLE STATEMENT
Title Random processes :
Sub Title filtering, estimation, and detection /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 PDF (xvii, 608 pages) :
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preface. -- Experiments and Probability. -- Random Variables. -- Estimation of Random Variables. -- Random Processes. -- Linear Systems: Random Processes. -- Nonlinear Systems: Random Processes. -- Optimum Linear Filters: The Wiener Approach. -- Optimum Linear Systems: The Kalman Approach. -- Detection Theory: Discrete Observation. -- Detection Theory: Continuous Observation. -- Appendix A. The Bilateral Laplace Transform. -- Appendix B. Table of Binomial Probabilities. -- Appendix C. Table of Discrete Random Variables and Properties. -- Appendix D. Table of Continuous Random Variables and Properties. -- Appendix E. Table of Gaussian Cumulative Distribution Function. -- Index.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Stochastic processes.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Image processing.
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5271182
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Hoboken, New Jersey :
-- Wiley-Interscience,
-- c2003.
264 #2 -
-- [Piscataqay, New Jersey] :
-- IEEE Xplore,
-- [2003]
336 ## -
-- text
-- rdacontent
337 ## -
-- electronic
-- isbdmedia
338 ## -
-- online resource
-- rdacarrier
588 ## -
-- Description based on PDF viewed 12/21/2015.
651 #7 - SUBJECT ADDED ENTRY--SUBJECT 2
-- Processos Estocasticos.
695 ## -
-- AWGN
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-- Additive white noise
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-- Approximation methods
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-- Artificial intelligence
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-- Concrete
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-- Continuous time systems
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-- Convergence
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-- Convolution
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-- Correlation
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-- Cost function
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-- Covariance matrix
695 ## -
-- Density functional theory
695 ## -
-- Distribution functions
695 ## -
-- Equations
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-- Estimation
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-- Extraterrestrial measurements
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-- Finite element methods
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-- Fourier transforms
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-- Frequency domain analysis
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-- Gaussian distribution
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-- Gaussian processes
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-- Indexes
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-- Indexing
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-- Information filters
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-- Integral equations
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-- Joints
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-- Kalman filters
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-- Kernel
695 ## -
-- Laplace equations
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-- Linear systems
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-- Mathematical model
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-- Maximum likelihood detection
695 ## -
-- Measurement uncertainty
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-- Nonlinear filters
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-- Nonlinear systems
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-- Pattern recognition
695 ## -
-- Power measurement
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-- Probability
695 ## -
-- Probability density function
695 ## -
-- Radar
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-- Random processes
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-- Random variables
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-- Strips
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-- Support vector machine classification
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-- Testing
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-- Time domain analysis
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-- Time measurement
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-- Time varying systems
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-- Transforms
695 ## -
-- Vectors

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