Overview
- 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 both in terms of theory applied to biomedical, industrial, and environmental problems
- Includes contributions by editors and contributors who are experts in their areas and are geographically diverse
- Includes supplementary material: sn.pub/extras
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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.
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Keywords
Table of contents (16 chapters)
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Collaborative Signal Processing Algorithms
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Knowledge Extraction in Brain Science
Editors and Affiliations
Bibliographic Information
Book Title: Signal Processing Techniques for Knowledge Extraction and Information Fusion
Editors: Danilo Mandic, Martin Golz, Anthony Kuh, Dragan Obradovic, Toshihisa Tanaka
DOI: https://doi.org/10.1007/978-0-387-74367-7
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag US 2008
Hardcover ISBN: 978-0-387-74366-0Published: 04 April 2008
Softcover ISBN: 978-1-4419-4495-5Published: 04 November 2010
eBook ISBN: 978-0-387-74367-7Published: 23 March 2008
Edition Number: 1
Number of Pages: XXII, 320
Topics: Signal, Image and Speech Processing, Communications Engineering, Networks, Data Mining and Knowledge Discovery