期刊文献+

一种基于峭度的一单元ICA-R固定点算法 被引量:3

Fixed-point algorithm based on kurtosis for one-unit ICA-R
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摘要 一单元参考独立成分分析是一种有效的利用先验信息抽取一个期望源信号的方法。以峭度的绝对值为对比函数推导出一种一单元ICA-R固定点算法,该算法避免了对比函数二阶导数的计算,简化了运算复杂度,比基于峭度的牛顿快速算法有更快的收敛速度。通过计算机模拟实验验证了算法的有效性。 One-unit ICA-R is an efficient method utilizing prior information to extract an expected source signal.A fixed-point algorithm for one-unit ICA-R is proposed when absolute value of kurtosis is considered as contrast function in this paper.The algorithm avoids the second derivative of contrast function and simpilifies operation accordingly.The fixed-point algorithm can converge faster than Newton fast algorithm based on kurtosis.At last,computer simulations verify the validity of the proposed algorithm.
机构地区 华北科技学院
出处 《计算机工程与应用》 CSCD 2012年第2期130-132,172,共4页 Computer Engineering and Applications
基金 国家自然科学基金(No.60672049)
关键词 峭度 固定点算法 参考独立成分分析 kurtosis fixed-point algorithm component analysis with reference
  • 相关文献

参考文献13

  • 1Hyvarinen A, Karhunen J, Oja E.Independent component analysis[M]. [S.I.]: John Wiley&Sons, Inc,2001.
  • 2Comon P.Independent component analysis: a new concept?[J].Signal Processing, 1994,36(3 ) : 287-314.
  • 3ell A J, Sejnowski T J.An information-maximization approach to blind separation and blind deconvolution[J].Neural Computation, 1995,7(6) : 1129-1159.
  • 4Cardoso J F, Laheld B H.Equivariant adaptive source separation[J]. IEEE Transactions on Signal Processing,1996,44(12):3017-3030.
  • 5Back A D.A first application of independent component analysis to extracting structure from stock returns[J].Neural Systems, 1997,8 (4) : 473-484.
  • 6Delfosse N, Loubaton P.Adaptive blind separation of independent sources: a deflation approach[J].Signal Processing, 1995,45 (1):59-83.
  • 7Hyva"rinen A, Oja E.A fast fixed-point algorithm for independent component analysis[J].Neural Computation, 1997,9(7) : 1483-1492.
  • 8Hyvarinen A.Fast and robust fixed-point algorithms for independent component analysis[J].IEEE Transactions on Neural Networks, 1999,10(3) :626-634.
  • 9Lu W, Rajapaks J C.Approach and applications of constrained ICA[J].IEEE Transactions on Neural Networks, 2005, 16(1): 203-212.
  • 10Lu W, Rajapakse J C.ICA with reference[J].Neurocomputing,2006,69(16/18):2244-2257.

二级参考文献12

  • 1Comon P.Independent component analysis:a new concept?[J].Signal Processing,1994,36(3):287-314.
  • 2Bell A J,Scjnowski T J.An information-maximization approach to blind separation and blind deconvolution[J].Neural Computation,1995,7(6):1129-1159.
  • 3Cardoso J F,Laheld B H.Equivariant adaptive source separation[J].IEEE Transactions on Signal Processing,1996,44(12):3017-3030.
  • 4Park H M,Jeong H Y,Lee T W,et al.Subband-based blind signal separation for noisy speech recognition[J].Electronics Letters,1999,35(23):2011-2012.
  • 5Back A D.A first application of independent component analysis to extracting structure from stock returns[J].Neural Systems,1997,8(4):473-484.
  • 6Delfosse N,Loubaton P.Adaptive blind separation of independent sources:a deflation approach[J].Signal Processing,1995,45(1):59-83.
  • 7Hyvarinen A,Oja E.A fast fixed-point algorithm for independent component analysis[J].Neural Computation,1997,9(7):1483-1492.
  • 8Hyvarinen A.Fast and robust fixed-point algorithms for independent component analysis[J].IEEE Transactions on Neural Networks,1999,10(3):626-634.
  • 9Lu W,Rajapakse J C.Appreach and applications of constrained ICA[J].IEEE Transactions on Neural Networks,2005,16(1):203-212.
  • 10Lu W,Rajapakse J C.ICA with reference[C]//Proc 3rd International Conference on Independent Component Analysis and Blind Source Scparation(ICA2001),San Diegn,California,2001:120-125.

共引文献7

同被引文献32

  • 1张荣,薛国民.修正的三次收敛的牛顿迭代法[J].大学数学,2005,21(1):80-82. 被引量:26
  • 2孙守宇,郑君里,吴里江,赵莹.峭度自适应学习率的盲信源分离[J].电子学报,2005,33(3):473-476. 被引量:11
  • 3王雪,张兴周,田金超.基于峭度的盲源分离方法研究[J].应用科技,2006,33(6):31-33. 被引量:2
  • 4Liu Ting-ting, Ren Xing-min.A Blind De-convolution Technique for Machine Fault Diagnosis [C]. 2009 Second International Conference on Information and Computing Science.Xi’an China:IEEE,2009:232-235.
  • 5李舜酩.转子振动信号的盲源分离研究[J].仪器仪表学报,2008,29(8):545-549.
  • 6Peter W. Tse, J. Y. Zhang , X. J. Wang. Blind Source Separation and Blind Equalization Algorithms for Mechanical Signal Separation and Identification[J]. Journal of Vibration and Contro,2006,12(4): 395-423.
  • 7Aapo Hyvarinen. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis[J].IEEE Trans.on Neural Networks,1999,10(3):626-634.
  • 8D. P. Acharya , G. Panda. A Review of Independent Component Analysis Techniques and their Applications[J]. IETE TECHNICAL REVIEW,2008,25(6)320-333.
  • 9A. Jime′nez-Gonza′lez , C. J. James. Extracting sources from noisy abdominal phonograms: a single-channel blind source separation method[J]. Med Biol Eng Comput ,2009, 47:655–664.
  • 10ELLA BINGHAM,AAPO HYV¨ARINEN. A FAST FIXED-POINT ALGORITHM FOR INDEPENDENT COMPONENT ANALYSIS OF COMPLEX VALUED SIGNALS[J], International Journal of Neural Systems,2000,10(1):1-8.

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二级引证文献6

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