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基于模糊聚類的信源個(gè)數(shù)檢測新算法

包志強(qiáng) 韓冰 吳順君

包志強(qiáng), 韓冰, 吳順君. 基于模糊聚類的信源個(gè)數(shù)檢測新算法[J]. 電子與信息學(xué)報(bào), 2006, 28(10): 1761-1765.
引用本文: 包志強(qiáng), 韓冰, 吳順君. 基于模糊聚類的信源個(gè)數(shù)檢測新算法[J]. 電子與信息學(xué)報(bào), 2006, 28(10): 1761-1765.
Bao Zhi-qiang, Han Bing, Wu Shun-jun. A New Source Number Detection Algorithm Based on Fuzzy Clustering[J]. Journal of Electronics & Information Technology, 2006, 28(10): 1761-1765.
Citation: Bao Zhi-qiang, Han Bing, Wu Shun-jun. A New Source Number Detection Algorithm Based on Fuzzy Clustering[J]. Journal of Electronics & Information Technology, 2006, 28(10): 1761-1765.

基于模糊聚類的信源個(gè)數(shù)檢測新算法

A New Source Number Detection Algorithm Based on Fuzzy Clustering

  • 摘要: 信源個(gè)數(shù)檢測方法的研究是目前陣列信號處理領(lǐng)域的一個(gè)研究熱點(diǎn)和重點(diǎn),它的測量精度直接影響到許多高分辨測向算法的精確度。然而現(xiàn)有的檢測方法對于不同的噪聲環(huán)境非常敏感;而且隨著快拍數(shù)的減少性能迅速下降?;谝陨系南拗婆c缺陷,該文提出了一種基于模糊c均值聚類的信源個(gè)數(shù)檢測方法。在兩種不同噪聲環(huán)境下的仿真結(jié)果表明該方法的有效性和魯棒性。
  • Schmidt R O. A signal subspace approach to multiple emitterlocation and spectrum estimation. [Ph.D. dissertation], Stanford Univ., Stanford, CA, 1981.[2]Wax M, Kailath T. Detection of signals by information theoretic criteria[J].IEEE Trans. on Acoustics, Speech, and Signal Processing.1985, 33(4):387-[3]Chen W, Wong K M, Reilly J P. Detection of the number ofsignals: A predicted eigen-threshold approach[J].IEEE Trans. on Signal Processing.1991, 39(5):1088-[4]Wu H T, Yang J F, Chen F K. Source number estimation using transformed Gershgorin radii[J].IEEE Trans. on Signal Processing.1995, 43(6):1325-[5]Aouada S, Zoubir A M, See C M S. Source detection in the presence of nonuniform noise. in Proc. ICASSP-2004, Montreal, Quebec, Canada, May 2004: II-165-II-168.[6]Chen W, Reilly JP, Wong K M. Detection of the number of signals in noise with banded covariance matrix. IEE Proc.-Radar. Sonar Navig., 1996, 143(10): 284.294.[7]Zhang Q T, Wang K M. Information theoretic criteria for the determination of the number of signals in spatially correlated noise. IEEE Trans. on Signal Processing, 1993, 41(8): 1651.1663.[8]Wu Y, Tam K W. On determination of the number of signals in spatially correlated noise[J].IEEE Trans. on Signal Processing.1998, 46(11):3023-[9]Wu Y, Tam K W, Li F. Determination of number of sources with multiple arrays in correlated noise fields[J].IEEE Trans. on SignalProcessing.2002, 50(6):1257-[10]Sheng C, Bernard M, Peter M G. A clustering technique for digital communications channel equalization using radial basis function networks[J].IEEE Trans. on Neural Networks.1993, 4(4):570-[11]Bezdek J C, Fordon W A. The Application of Fuzzy Set Theory to the Medical Diagnosis. In Advances of Fuzzy Sets and Theories, North-Holland, Amsterdam, 1979: 445.461.[12]Karayiannis N B, Mi G W. Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques. IEEE Trans. on NN, 1997, 8(6): 1492.1506.[13]Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithm. New York: Plenum Press, 1981: 43.93.
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  • 收稿日期:  2005-04-11
  • 修回日期:  2005-09-07
  • 刊出日期:  2006-10-19

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