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Books > Computing & IT > Applications of computing > Signal processing
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Bayesian Signal Processing - Classical, Modern, and Particle Filtering Methods 2e (Hardcover, 2nd Edition)
Loot Price: R3,597
Discovery Miles 35 970
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Bayesian Signal Processing - Classical, Modern, and Particle Filtering Methods 2e (Hardcover, 2nd Edition)
Expected to ship within 10 - 15 working days
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Presents the Bayesian approach to statistical signal processing for
a variety of useful model sets This book aims to give readers a
unified Bayesian treatment starting from the basics (Baye s rule)
to the more advanced (Monte Carlo sampling), evolving to the
next-generation model-based techniques (sequential Monte Carlo
sampling). This next edition incorporates a new chapter on
Sequential Bayesian Detection, a new section on Ensemble Kalman
Filters as well as an expansion of Case Studies that detail
Bayesian solutions for a variety of applications. These studies
illustrate Bayesian approaches to real-world problems incorporating
detailed particle filter designs, adaptive particle filters and
sequential Bayesian detectors. In addition to these major
developments a variety of sections are expanded to fill-in-the gaps
of the first edition. Here metrics for particle filter (PF) designs
with emphasis on classical sanity testing lead to ensemble
techniques as a basic requirement for performance analysis. The
expansion of information theory metrics and their application to PF
designs is fully developed and applied. These expansions of the
book have been updated to provide a more cohesive discussion of
Bayesian processing with examples and applications enabling the
comprehension of alternative approaches to solving
estimation/detection problems. The second edition of Bayesian
Signal Processing features: * Classical Kalman filtering for
linear, linearized, and nonlinear systems; modern unscented and
ensemble Kalman filters: and the next-generation Bayesian particle
filters * Sequential Bayesian detection techniques incorporating
model-based schemes for a variety of real-world problems *
Practical Bayesian processor designs including comprehensive
methods of performance analysis ranging from simple sanity testing
and ensemble techniques to sophisticated information metrics * New
case studies on adaptive particle filtering and sequential Bayesian
detection are covered detailing more Bayesian approaches to applied
problem solving * MATLAB(R) notes at the end of each chapter help
readers solve complex problems using readily available software
commands and point out other software packages available * Problem
sets included to test readers knowledge and help them put their new
skills into practice Bayesian Signal Processing, Second Edition is
written for all students, scientists, and engineers who investigate
and apply signal processing to their everyday problems.
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