Signal Processing Techniques for Knowledge Extraction and Information Fusion [Paperback]

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.

Collaborative Signal Processing Algorithms.- Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion.- Wind Modelling and its Possible Application to Control of Wind Farms.- Hierarchical Filters in a Collaborative Filtering Framework for System Identification and Knowledge Retrieval.- Acoustic Parameter Extraction From Occupied Rooms Utilizing Blind Source Separation.- Signal Processing for Source Localization.- Sensor Network Localization Using Least Squares Kernel Regression.- Adaptive Localization in Wireless Networks.- Signal Processing Methods for Doppler Radar Heart Rate Monitoring.- Multimodal Fusion for Car Navigation Systems.- Information Fusion in Imaging.- Cue and Sensor Fusion for Independent Moving Objects Detection and Description in Driving Scenes.- Distributed Vision Networks for Human Pose Analysis.- Skin Color Separation and Synthesis for E-Cosmetics.- ICA for Fusion of Brain Imaging Data.- Knowledge Extraction in Brain Science.- Complex Empirical Mode Decomposition for Multichannel Information Fusion.- Information Fusion for Perceptual Feedback: A Brain Activity Sonification Approach.- Advanced EEG Signal Processing in Brain Death Diagnosis.- Automatic Knowledge Extraction: Fusion of Human Expert Ratings and Biosignal Features for Fatigue Monitoring Applications.

This state-of-the-art resource brings together the latest findings from the cross-fertilization of signal processing, machine learning and computer science. lS,