Advances in Intelligent Signal Processing and Data Mining: Theory and Applications [Paperback]

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis.

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The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.

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From the content: Introduction to Intelligent Signal Processing and Data Mining.- Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning.- A Sequential Monte Carlo Method for Multi-Target Tracking with the Intensity Filter.- Sequential Monte Carlo Methods forLocalisation inWireless Networks.- A Sequential Monte Carlo Approach for Brain Source Localization.

From the reviews:

This book is well structured and provides good coverage of several state-of-the-art approaches to intelligent signal processing and data mining. & chapters contain examples and algorithms and are accompanied by useful illustrations (several of which are in color) that help to explain the described approaches. The audience for the book is researchers and practitioners in signal processing and data mining who are interested in the latest developments in these areas. (Aris Gkoulalas-Divanis, Computing Reviews, May, 2013)

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range fromlC¼