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Title Advances in intelligent signal processing and data mining : theory and applications / Petia Georgieva, Lyudmila Mihaylova, and Lakhmi C. Jain (eds.)
Published Berlin ; New York : Springer, [2013]
©2013
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Description 1 online resource
Series Studies in computational intelligence, 1860-949X ; 410
Studies in computational intelligence ; 410
Contents Introduction to Intelligent Signal Processing and Data Mining / Lyudmila Mihaylova, Petia Georgieva and Lakhmi C. Jain -- Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning / Avishy Y. Carmi, Lyudmila Mihaylova, Amadou Gning, Pini Gurfil and Simon J. Godsill -- A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter / Marek Schikora, Wolfgang Koch, Roy Streit and Daniel Cremers -- Sequential Monte Carlo Methods for Localization in Wireless Networks / Lyudmila Mihaylova, Donka Angelova and Anna Zvikhachevskaya -- A Sequential Monte Carlo Approach for Brain Source Localization / Petia Georgieva, Lyudmila Mihaylova, Filipe Silva, Mariofanna Milanova and Nuno Figueiredo, et al. -- Computational Intelligence in Automotive Applications / Yifei Wang, Naim Dahnoun and Alin Achim -- Detecting Anomalies in Sensor Signals Using Database Technology / Gereon Schüller, Andreas Behrend and Wolfgang Koch -- Hierarchical Clustering for Large Data Sets / Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton and Badrinath Roysam -- A Novel Framework for Object Recognition under Severe Occlusion / Stamatia Giannarou and Tania Stathaki -- Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis / Hans-Georg Zimmermann, Christoph Tietz and Ralph Grothmann -- Reinforcement Learning with Neural Networks: Tricks of the Trade / Christopher J. Gatti and Mark J. Embrechts -- Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling / A. Zeiler, R. Faltermeier, A.M. Tomé, I.R. Keck and C. Puntonet, et al
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
Analysis Engineering
Artificial intelligence
Bibliography Includes bibliographical references and author index
Subject Signal processing -- Digital techniques -- Data processing.
Data mining.
Form Electronic book
Author Georgieva, Petia (Lecturer in signal processing)
Mihaylova, Lyudmila.
Jain, L. C.
ISBN 364228695X (print)
3642286968 (electronic bk.)
9783642286957 (print)
9783642286964 (electronic bk.)