Multisensor Processing for Signal Extraction and Applications
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Editorial MultiSensor Processing for Signal Extraction and Applications Chong-Yung Chi,1 Ta-Sung Lee,2 Zhi-Quan Luo,3 Yue Wang,4 and Kung Yao5 1 Institute
of Communications Engineering, and Department of Electrical Engineering, National Tsing Hua University, 101, Sec. 2, Kuang Fu Road, Hsinchu, Taiwan 30013 2 Department of Communication Engineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300 3 Department of Electrical and Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, MN 55455, USA 4 Computational Bioinformatics and Bioimaging Laboratory, Advanced Research Institute, 4300 Wilson Boulevard, Suite 750, Arlington, VA 22203, USA 5 Electrical Engineering Department, University of California, Los Angeles, CA 90095, USA Received 29 August 2006; Accepted 29 August 2006 Copyright © 2006 Chong-Yung Chi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Source signal extraction from heterogeneous measurements has a wide range of applications in many scientific and technological fields, for example, digital communication, speech and acoustic signal processing, as well as biomedical pattern analysis. In these applications, the use of a multisensor system allows simultaneous reception of multiple signals which, when appropriately processed, can deliver significant performance improvement over a single-sensor system. A key component of any multisensor system is the signal processing module which ideally should maximally exploit the diversity present in the multiple received copies of the mixed source signals. The ultimate goal of multisensor signal processing is to offer robust high quality signal extraction under realistic assumptions with minimal computational complexity. Despite continued progress in the past few decades, multisensor-based signal processing techniques have remained a major research focus of the signal processing community. Currently there are major on-going research efforts in high quality signal extraction, realistic theoretical modeling of real-world problems, algorithm complexity reduction, and efficient real-time implementation. In response to the growing interest from industry, academia, and government agencies in the research and development of multisensor signal processing systems, this special issue is edited so as to provide a snapshot of the state-of-the-art in multisensor signal processing research. This special issue is composed of four groups of contributions on signal extraction for multiple-input multipleoutput systems (channels) and applications. The first group consists of one paper (by I. Kacha et al.) studying the
equalizer design of a multichannel FIR system with emphases on low computational complexity and robustness to channel conditions, and two papers (by C.-H. Peng et al. and by X. Zheng et al., resp.) exhibiting performance gain (in terms of output signal to
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