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Advances in Intelligent Signal Processing and Data Mining

Theory and Applications

  • Book
  • © 2013

Overview

Editors:
  1. Petia Georgieva

    1. , Dep. of Electronics Telecommunications, University of Aveiro, Aveiro, Portugal

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  2. Lyudmila Mihaylova

    1. , School of Computing and Communications, Lancaster University, Lancaster, Montserrat

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Lakhmi C Jain

    1. , School of Electrical and Information, University of South Australia, Adelaide, Australia

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    You can also search for this editor in PubMed   Google Scholar

  • Computational Intelligence applied to engineering
  • Latest research on security and sensor networks in complex engineering systems
  • Written by leading experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 410)

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Table of contents (12 chapters)

  1. Front Matter

    Pages 1-12
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  2. Introduction to Intelligent Signal Processing and Data Mining

    • Lyudmila Mihaylova, Petia Georgieva, Lakhmi C. Jain
    Pages 1-5

  3. Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning

    • Avishy Y. Carmi, Lyudmila Mihaylova, Amadou Gning, Pini Gurfil, Simon J. Godsill
    Pages 7-53

  4. A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter

    • Marek Schikora, Wolfgang Koch, Roy Streit, Daniel Cremers
    Pages 55-87

  5. Sequential Monte Carlo Methods for Localization in Wireless Networks

    • Lyudmila Mihaylova, Donka Angelova, Anna Zvikhachevskaya
    Pages 89-118

  6. A Sequential Monte Carlo Approach for Brain Source Localization

    • Petia Georgieva, Lyudmila Mihaylova, Filipe Silva, Mariofanna Milanova, Nuno Figueiredo, Lakhmi C. Jain
    Pages 119-138

  7. Computational Intelligence in Automotive Applications

    • Yifei Wang, Naim Dahnoun, Alin Achim
    Pages 139-174

  8. Detecting Anomalies in Sensor Signals Using Database Technology

    • Gereon Schüller, Andreas Behrend, Wolfgang Koch
    Pages 175-196

  9. Hierarchical Clustering for Large Data Sets

    • Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton, Badrinath Roysam
    Pages 197-233

  10. A Novel Framework for Object Recognition under Severe Occlusion

    • Stamatia Giannarou, Tania Stathaki
    Pages 235-258

  11. Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis

    • Hans-Georg Zimmermann, Christoph Tietz, Ralph Grothmann
    Pages 259-274

  12. Reinforcement Learning with Neural Networks: Tricks of the Trade

    • Christopher J. Gatti, Mark J. Embrechts
    Pages 275-310

  13. Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling

    • A. Zeiler, R. Faltermeier, A. M. Tomé, I. R. Keck, C. Puntonet, A. Brawanski et al.
    Pages 311-349

  14. Back Matter

    Pages 0--1
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Keywords

About this book

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.

 

Reviews

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)

Editors and Affiliations

  • , Dep. of Electronics Telecommunications, University of Aveiro, Aveiro, Portugal

    Petia Georgieva

  • , School of Computing and Communications, Lancaster University, Lancaster, Montserrat

    Lyudmila Mihaylova

  • , School of Electrical and Information, University of South Australia, Adelaide, Australia

    Lakhmi C Jain

Bibliographic Information

  • Book Title: Advances in Intelligent Signal Processing and Data Mining

  • Book Subtitle: Theory and Applications

  • Editors: Petia Georgieva, Lyudmila Mihaylova, Lakhmi C Jain

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-28696-4

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2013

  • Hardcover ISBN: 978-3-642-28695-7Published: 27 July 2012

  • Softcover ISBN: 978-3-642-43980-3Published: 09 August 2014

  • eBook ISBN: 978-3-642-28696-4Published: 27 July 2012

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 354

  • Topics: Engineering, general, Artificial Intelligence

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