Signal Processing Techniques for Knowledge Extraction and Information Fusion

Editors: Mandic, D., Golz, M., Kuh, A., Obradovic, D., Tanaka, T. (Eds.)

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  • Presents knowledge extraction and information fusion supported by state-of-the-art background material
  • Brings together cutting edge research, both theoretical and applied, and reflects the state-of-the-art of both in terms of theory applied to biomedical, industrial, and environmental problems
  • Includes contributions from experts in their areas who are geographically diverse
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eBook $129.00
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  • ISBN 978-0-387-74367-7
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Hardcover $219.99
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Softcover $169.99
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About this book

This state-of-the-art resource brings together the latest findings from the cross-fertilization of signal processing, machine learning and computer science.  The emphasis is on demonstrating synergy of different signal processing methods with knowledge extraction and heterogeneous information fusion. Issues related to the processing of signals with low signal-to-noise ratio, solving real-world multi-channel problems, and using adaptive techniques where nonstationarity, uncertainty and complexity play major roles are addressed.  Particular methods include Independent Component Analysis, Support Vector Machines, Distributed and Collaborative Adaptive Filtering, Empirical Mode Decomposition, Self Organizing Maps, Fuzzy Logic, Evolutionary Algorithms and several others used frequently in these fields.  Also included are both important and novel applications from telecommunications, renewable energy and biomedical engineering.

Signal Processing Techniques for Knowledge Extraction and Information Fusion which proposes new techniques for extracting knowledge based on combining heterogeneous information sources is an excellent reference for professionals in signal and image processing, machine learning, data and sensor fusion, computational intelligence, knowledge discovery, pattern recognition, and environmental science and engineering.

Table of contents (16 chapters)

Table of contents (16 chapters)
  • Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion

    Pages 3-21

    Jelfs, Beth (et al.)

  • Wind Modelling and its Possible Application to Control of Wind Farms

    Pages 23-36

    Hirata, Yoshito (et al.)

  • Hierarchical Filters in a Collaborative Filtering Framework for System Identification and Knowledge Retrieval

    Pages 37-54

    Boukis, Christos (et al.)

  • Acoustic Parameter Extraction From Occupied Rooms Utilizing Blind Source Separation

    Pages 55-74

    Zhang, Yonggang (et al.)

  • Sensor Network Localization Using Least Squares Kernel Regression

    Pages 77-96

    Kuh, Anthony (et al.)

Buy this book

eBook $129.00
price for USA in USD
  • ISBN 978-0-387-74367-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $219.99
price for USA in USD
  • ISBN 978-0-387-74366-0
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
Softcover $169.99
price for USA in USD
  • ISBN 978-1-4419-4495-5
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Signal Processing Techniques for Knowledge Extraction and Information Fusion
Editors
  • Danilo Mandic
  • Martin Golz
  • Anthony Kuh
  • Dragan Obradovic
  • Toshihisa Tanaka
Copyright
2008
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-74367-7
DOI
10.1007/978-0-387-74367-7
Hardcover ISBN
978-0-387-74366-0
Softcover ISBN
978-1-4419-4495-5
Edition Number
1
Number of Pages
XXII, 320
Topics