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A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices

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2005
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Conference Paper

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Liu, Xianhua and Randall, R.B. 2005. A New Independent Component Analysis Algorithm: Joint Approximate Diagonalization of Simplified Cumulant Matrices, in Bachor H.A. and Massimiliano, C. (ed), Proceedings of The 16th Biennial Congress of the Australian Institute of Physics - "Physics for the Nation", Jan 31-Feb 4 2005, pp. 29-32. Canberra, Australia: Australian Institute of Physics.
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Proceedings of the 16th National Congress of Australian Institute of Physics
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The 16th National Congress of Australian Institute of Physics 2005
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Abstract

This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the separation cost for large-scale problems. Experimental separation shows that the new algorithm is robust, reliable and efficient for both large and small-scale separation problems, thus has combined merits of the well-known JADE and Fast ICA algorithms. Mixed music and speech signal separation is presented in this paper.