Journal of Guangdong University of Technology ›› 2007, Vol. 24 ›› Issue (4): 38-41.

• Comprehensive Studies • Previous Articles     Next Articles

A New ICA Algorithm Based on Normalized Kurtosis

  

  1. (Faculty of Applied Mathematics,Guangdong University of Technology,Guangzhou 510006,China)
  • Online:2007-11-08 Published:2007-11-08

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Abstract: The traditional approach to gradient to search for the cost function’s extreme in the independent component analysis was based on kurtosis.The path we are looking for is crucial to the convergence of the algorithm.In the Kuicnet algorithm,after replacing the gradient of the cost function with its scaling we obtained a new ICA algorithm.Adjusting the path of the gradient timely in the iterative process,it accelerates the convergence.The simulation illustrates the effectiveness.

Key words: independent component analysis； kurtosis； fast-ICA algorithm；

[1] DOUGLAS S C,KUNG S Y.Kuicnet algorithms for blinddecon-volution. IEEE Workshop Neural Networks Sig-nal Process Cambridge . 1998

[2] HYVARINEN A,OJA E.Independent Component Analy-sis:Algorithms and Application. Neural Networks Cen-tre . 2000

[3] GEORGIE P,CICHOCKI A,AMARI S.On some exten-sions of the natural gradient algorithm. Third Interna-tional Conference on Independent Component Analysis andBlind Signal Separation(ICA 2001) . 2001

[4] HYVARINEN A,KARHUNEN J,OJA E.Independentcomponent analysis. . 2001

[5] JUTTEN C.Blind separation of sources. Signal Processing . 1991

[6] COMON P.Independent component analysis,a new con-cept. Signal Processing . 1994

[7] Lee T W.Independent component analysis using an extended infomax algorithm for mixed subgaussion and supergaussion sources. Neural Computation . 1999

[8] Hyv rinen A.Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks . 1999
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