Signal Processing Techniques for Knowledge Extraction and Information Fusion
Language: English
Published by Springer US, 2010
- Softcover
- New
Condition: New
£ 119.53
Quantity: Over 20 available
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents knowledge extraction and information fusion supported by state of the art background materialBrings together cutting edge research, both theoretical and applied, and reflects the state of the art both in terms of theory applied to biomedi.
Seller Inventory # 4174843
- Title
- Signal Processing Techniques for Knowledge Extraction and Information Fusion
- Author
- Mandic, Danilo|Golz, Martin|Kuh, Anthony|Obradovic, Dragan|Tanaka, Toshihisa
- Publisher
- Springer US
- Publication year
- 2010
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1441944958
- ISBN 13
- 9781441944955
This book brings together the latest research achievements from various areas of signal processing and related disciplines. It aims to present knowledge extraction and information fusion supported by state-of-the-art background material. Within the book contributions presenting both novel algorithms and existing applications, especially those (but not restricted to) on-line processing of real world data are included. The areas of Knowledge Extraction and Information Fusion are naturally linked, and the subject is of major interest for modern biomedical, environmental, and industrial applications. This provides the state-of-the-art and proposes new techniques in order to combine heterogeneous information sources.
"Synopsis" may belong to another edition of this title.
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 the title" may belong to another edition of this title.
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