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一种奇异混合信号盲分离的神经网络模型 被引量:1

A Kind of Neural Network Model for Blind Separation of Singularly Mixed Sources
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摘要 混合信号盲分离问题是一类很难而又具有很强应用背景的问题 ,以往对这类问题的研究均在混合矩阵为非奇异的条件下进行 .本文给出一种神经网络模型及相应算法 。 Blind separation of sources is a problem arising in many practical fields, which is difficult to research. In the existing references, the mixing matrix of sources is always supposed to be nonsingular. This paper presents an algorithm and a corresponding networks to deal with blind separation of sources in the case of singular mixing matrix.
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2001年第1期105-108,共4页 Control Theory & Applications
基金 国家自然科学基金重点基金! (6 95 740 0 9) 国家自然科学基金! (6 0 0 0 40 0 4) 广东省自然科学基金! (990 5 84)资助项目
关键词 信号盲分离 奇异性 神经网络 噪声 信号处理 blind separation singularity neural networks noise
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参考文献5

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同被引文献14

  • 1白琳,陈豪.一种奇异混合阵的盲信号提取算法[J].空间电子技术,2012,9(1):6-10. 被引量:1
  • 2王世海,陈向东,毕雪,杨家德,卢文韬.多分辨率子带分解的独立分量分析算法在红外图像去噪上的应用[J].电子技术应用,2007,33(6):66-68. 被引量:1
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  • 6HYVARINEN A, PAJUNEN P. Nonlinear independent component analysis: Existence and uniqueness results[J]. Neural Networks, 1999, 12(3) : 429-439.
  • 7JUTYEN C, ZADEH M, HOSSEINI S. Three easy ways for separating nonlinear mixtures[J]. Signal Processing, 2004, 84 (2) : 217- 229.
  • 8LIU W, RAJAPAKSE J. Approach and applications of constrained ICA[J]. Trans Neural Networks, 2005, 16( 1 ) : 203-212.
  • 9PLUMBLEY M. Algorithms for nonnegative component independent analysis[J]. Trans Neural Networks, 2003, 14(3) : 534-543.
  • 10LEE T, LEWICKI M, GIROLAMI M, et al. Blind source separation of more sources than mixtures using over-complete representations[J]. Signal Processing Letters, 1999, 4(5): 205-208.

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