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Bayesian signal processing classical, modern, and particle filtering methods /

New Bayesian approach helps you solve tough problems in signal processing with ease. Signal processing is based on this fundamental conceptthe extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when...

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Bibliographic Details
Main Authors: Candy, J. V
Corporate Authors: Wiley InterScience Online service
Published:
Literature type: Electronic eBook
Language: English
Series: Adaptive and learning systems for signal processing, communications, and control
Subjects:
Signal processing > Mathematics
Bayesian statistical decision theory
Signal processing / Mathematics
COMPUTERS > Information Theory
TECHNOLOGY & ENGINEERING > Signals & Signal Processing
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9780470430583
Summary: New Bayesian approach helps you solve tough problems in signal processing with ease. Signal processing is based on this fundamental conceptthe extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when these assumptions are erroneous? Bayesian techniques circumvent this limitation by offering a completely different approach that can easily incorporate non-Gaussian and nonlinear processes along with all of the usual methods currently available. This text enables readers to fully exploit the many
Carrier Form: 1 online resource (xxiii, 445 p.) : ill., map.
Bibliography: Includes bibliographical references and index.
ISBN: 9780470430583
0470430583
9781118210543
1118210549
0470180943
9780470180945
9780470430576 (electronic bk.)
0470430575 (electronic bk.)
Index Number: TK5102
CLC: TN911.1
Contents: Bayestian estimation -- Simulation-based Bayesian methods -- State-space models for Bayesian processing -- Classical Bayesian state-space processors -- Modern Bayesian state-space processors -- Particle-based Bayesian state-space processors -- Joint Bayesian state/parametric processors -- Discrete hidden Markov model Bayesian processors -- Bayesian processors for physics-based applications.

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