Advances in Intelligent Signal Processing and Data Mining

Theory and Applications

  • Petia Georgieva
  • Lyudmila Mihaylova
  • Lakhmi C Jain

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

Table of contents

  1. Front Matter
    Pages 1-12
  2. Lyudmila Mihaylova, Petia Georgieva, Lakhmi C. Jain
    Pages 1-5
  3. Avishy Y. Carmi, Lyudmila Mihaylova, Amadou Gning, Pini Gurfil, Simon J. Godsill
    Pages 7-53
  4. Marek Schikora, Wolfgang Koch, Roy Streit, Daniel Cremers
    Pages 55-87
  5. Lyudmila Mihaylova, Donka Angelova, Anna Zvikhachevskaya
    Pages 89-118
  6. Petia Georgieva, Lyudmila Mihaylova, Filipe Silva, Mariofanna Milanova, Nuno Figueiredo, Lakhmi C. Jain
    Pages 119-138
  7. Yifei Wang, Naim Dahnoun, Alin Achim
    Pages 139-174
  8. Gereon Schüller, Andreas Behrend, Wolfgang Koch
    Pages 175-196
  9. Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton, Badrinath Roysam
    Pages 197-233
  10. Stamatia Giannarou, Tania Stathaki
    Pages 235-258
  11. Hans-Georg Zimmermann, Christoph Tietz, Ralph Grothmann
    Pages 259-274
  12. Christopher J. Gatti, Mark J. Embrechts
    Pages 275-310
  13. 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

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.



Advanced Computational Intelligence Computational Intelligence Engineering Applications Paradigms

Editors and affiliations

  • Petia Georgieva
    • 1
  • Lyudmila Mihaylova
    • 2
  • Lakhmi C Jain
    • 3
  1. 1., Dep. of Electronics TelecommunicationsUniversity of AveiroAveiroPortugal
  2. 2., School of Computing and CommunicationsLancaster UniversityLancasterMontserrat
  3. 3., School of Electrical and InformationUniversity of South AustraliaAdelaideAustralia

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-28695-7
  • Online ISBN 978-3-642-28696-4
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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