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Signal Processing Techniques for Knowledge Extraction and Information Fusion

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  • © 2008

Overview

Editors:
  1. Danilo Mandic

    1. Imperial College London, London, UK

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  2. Martin Golz

    1. University of Applied Sciences, Schmalkalden, Germany

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  3. Anthony Kuh

    1. University of Hawaii, Honolulu, USA

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  4. Dragan Obradovic

    1. Siemens AG, Munich, Germany

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  5. Toshihisa Tanaka

    1. Tokyo University of Agriculture and Technology, Japan

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  • Presents knowledge extraction and information fusion supported by state of the art background material
  • Brings together cutting edge research, both theoretical and applied, and reflects the state of the art both in terms of theory applied to biomedical, industrial, and environmental problems
  • Includes contributions by editors and contributors who are experts in their areas and are geographically diverse
  • Includes supplementary material: sn.pub/extras

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Table of contents (16 chapters)

  1. Front Matter

    Pages I-XXII
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  2. Collaborative Signal Processing Algorithms

    1. Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion

      • Beth Jelfs, Phebe Vayanos, Soroush Javidi, Vanessa Su Lee Goh, Danilo Mandic
      Pages 3-21

    2. Wind Modelling and its Possible Application to Control of Wind Farms

      • Yoshito Hirata, Hideyuki Suzuki, Kazuyuki Aihara
      Pages 23-36

    3. Hierarchical Filters in a Collaborative Filtering Framework for System Identification and Knowledge Retrieval

      • Christos Boukis, Anthony G. Constantinides
      Pages 37-54

    4. Acoustic Parameter Extraction From Occupied Rooms Utilizing Blind Source Separation

      • Yonggang Zhang, Jonathon A. Chambers
      Pages 55-74

  3. Signal Processing for Source Localization

    1. Sensor Network Localization Using Least Squares Kernel Regression

      • Anthony Kuh, Chaopin Zhu
      Pages 77-96

    2. Adaptive Localization in Wireless Networks

      • Henning Lenz, Bruno Betoni Parodi, Hui Wang, Andrei Szabo, Joachim Bamberger, Dragan Obradovic et al.
      Pages 97-120

    3. Signal Processing Methods for Doppler Radar Heart Rate Monitoring

      • Anders Høst-Madsen, Nicolas Petrochilos, Olga Boric-Lubecke, Victor M. Lubecke, Byung-Kwon Park, Qin Zhou
      Pages 121-140

    4. Multimodal Fusion for Car Navigation Systems

      • Dragan Obradovic, Henning Lenz, Markus Schupfner, Kai Heesche
      Pages 141-158

  4. Information Fusion in Imaging

    1. Cue and Sensor Fusion for Independent Moving Objects Detection and Description in Driving Scenes

      • Nikolay Chumerin, Marc M. Van Hulle
      Pages 161-180

    2. Distributed Vision Networks for Human Pose Analysis

      • Hamid Aghajan, Chen Wu, Richard Kleihorst
      Pages 181-200

    3. Skin Color Separation and Synthesis for E-Cosmetics

      • Norimichi Tsumura, Nobutoshi Ojima, Toshiya Nakaguchi, Yoichi Miyake
      Pages 201-220

    4. ICA for Fusion of Brain Imaging Data

      • Vince D. Calhoun, Tülay Adali
      Pages 221-240

  5. Knowledge Extraction in Brain Science

    1. Complex Empirical Mode Decomposition for Multichannel Information Fusion

      • Danilo Mandic, George Souretis, Wai Yie Leong, David Looney, Marc M. Van Hulle, Toshihisa Tanaka
      Pages 243-260

    2. Information Fusion for Perceptual Feedback: A Brain Activity Sonification Approach

      • Tomasz M. Rutkowski, Andrzej Cichocki, Danilo Mandic
      Pages 261-273

    3. Advanced EEG Signal Processing in Brain Death Diagnosis

      • Jianting Cao, Zhe Chen
      Pages 275-298

    4. Automatic Knowledge Extraction: Fusion of Human Expert Ratings and Biosignal Features for Fatigue Monitoring Applications

      • Martin Golz, David Sommer
      Pages 299-316

  6. Back Matter

    Pages 317-320
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Keywords

About this book

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.

Editors and Affiliations

  • Imperial College London, London, UK

    Danilo Mandic

  • University of Applied Sciences, Schmalkalden, Germany

    Martin Golz

  • University of Hawaii, Honolulu, USA

    Anthony Kuh

  • Siemens AG, Munich, Germany

    Dragan Obradovic

  • Tokyo University of Agriculture and Technology, Japan

    Toshihisa Tanaka

Bibliographic Information

  • Book Title: Signal Processing Techniques for Knowledge Extraction and Information Fusion

  • Editors: Danilo Mandic, Martin Golz, Anthony Kuh, Dragan Obradovic, Toshihisa Tanaka

  • DOI: https://doi.org/10.1007/978-0-387-74367-7

  • Publisher: Springer New York, NY

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag US 2008

  • Hardcover ISBN: 978-0-387-74366-0Published: 04 April 2008

  • Softcover ISBN: 978-1-4419-4495-5Published: 04 November 2010

  • eBook ISBN: 978-0-387-74367-7Published: 23 March 2008

  • Edition Number: 1

  • Number of Pages: XXII, 320

  • Topics: Signal, Image and Speech Processing, Communications Engineering, Networks, Data Mining and Knowledge Discovery

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