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Advances in intelligent signal processing and data mining : theory and applications /

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 Carl...

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Bibliographic Details
Corporate Authors: SpringerLink (Online service)
Group Author: Georgieva, Petia; Mihaylova, Lyudmila; Jain, L. C.
Published: Springer,
Publisher Address: Berlin ; New York :
Publication Dates: 2013.
Literature type: eBook
Language: English
Series: Studies in computational intelligence, 410
Subjects:
Signal processing > Digital techniques > Data processing.
Data mining.
Signal processing > Data processing. > Data processing.
Engineering.
Artificial intelligence.
Electronic books.
Online Access: http://dx.doi.org/10.1007/978-3-642-28696-4
Summary: 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. 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.
Carrier Form: 1 online resource.
Bibliography: Includes bibliographical references and author index.
ISBN: 9783642286964 (electronic bk.)
3642286968 (electronic bk.)
Index Number: TK5102
CLC: TN911.7
Contents: 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 for Localization in Wireless Networks /
A Sequential Monte Carlo Approach for Brain Source Localization /
Computational Intelligence in Automotive Applications /
Detecting Anomalies in Sensor Signals Using Database Technology /
Hierarchical Clustering for Large Data Sets /
A Novel Framework for Object Recognition under Severe Occlusion /
Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis /
Reinforcement Learning with Neural Networks: Tricks of the Trade /
Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling /

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