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Signal Processing Techniques for Knowledge Extraction and Information Fusion (Information Technology: Transmission, Processing and Storage) - Hardcover
Synopsis
This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.
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From the Back Cover
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.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2008
- ISBN 10 0387743669
- ISBN 13 9780387743660
- BindingHardcover
- LanguageEnglish
- Number of pages342
- EditorMandic Danilo, Golz Martin, Kuh Anthony, Obradovic Dragan, Tanaka Toshihisa
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This state-of-the-art resourcebrings together the latest findingsfrom the cross-fertilization of signal processing, machine learningand 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 othersused frequently in thesefields. Also included arebothimportant and novel applications from telecommunications, renewable energy and biomedical engineering.Signal Processing Techniques for Knowledge Extraction and Information Fusionwhich 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. 320 pp. Englisch. Seller Inventory # 9780387743660
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