Advances in Intelligent Signal Processing and Data Mining: Theory and Applications

✍ Scribed by Lyudmila Mihaylova, Petia Georgieva (auth.), Petia Georgieva, Lyudmila Mihaylova, Lakhmi C Jain (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2013
• Tongue: English
• Leaves: 358
• Series: Studies in Computational Intelligence 410
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages 1-12
Introduction to Intelligent Signal Processing and Data Mining....Pages 1-5
Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning....Pages 7-53
A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter....Pages 55-87
Sequential Monte Carlo Methods for Localization in Wireless Networks....Pages 89-118
A Sequential Monte Carlo Approach for Brain Source Localization....Pages 119-138
Computational Intelligence in Automotive Applications....Pages 139-174
Detecting Anomalies in Sensor Signals Using Database Technology....Pages 175-196
Hierarchical Clustering for Large Data Sets....Pages 197-233
A Novel Framework for Object Recognition under Severe Occlusion....Pages 235-258
Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis....Pages 259-274
Reinforcement Learning with Neural Networks: Tricks of the Trade....Pages 275-310
Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling....Pages 311-349
Back Matter....Pages 0--1

✦ Subjects

Engineering, general; Artificial Intelligence (incl. Robotics)