Signal Processing Techniques for Knowledge Extraction and Information Fusion

By: Danilo Mandic, ?Martin Golz, ?Anthony Kuh

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eText | 23 March 2008 | Edition Number 1

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This book brings together the latest research achievements from various areas of signal processing and related disciplines in order to consolidate the existing and proposed new directions in DSP based knowledge extraction and information fusion. 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 aim at detecting and estimating the signal of interest and its parameters, and further at combining measurements from multiple sensors (and associated databases if appropriate) to achieve improved accuracies and more specific inferences which cannot be achieved by using only a single signal modality. The subject therefore is of major interest for modern biomedical, environmental, and industrial applications to provide a state of the art and propose new techniques in order to combine heterogeneous information sources.