Signal Processing Techniques for Knowledge Extraction and Information Fusion
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....
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer US
2008, 2008
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| Edition: | 1st ed. 2008 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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