An Iterative Inversion Approach to Blind Source Separation  

Oleh:

Ribas, L. Castedo ; Andrej, Cichocki ; Cruces-Alvarez, S. ; Cichocki, A. ; Castedo-Ribas, L.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 6 (2000), page 1423-1437.
Topik: SEPARATION; iterative; inversion; blind source; separation

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We present an iterative inversion (II) approach to blind source separation (BSS). It consists of a quasi - Newton method for the resolution of an estimating equation obtained from the implicit inversion of a robust estimate of the mixing system. The resulting learning rule includes several existing algorithms for BSS as particular cases giving them a novel and unified interpretation. It also provides a justification of the Cardoso and Laheld (1996) step size normalization. The II method is first presented for instantaneous mixtures and then extended to the problem of blind separation of convolutive mixtures. Finally, we derive the necessary and sufficient asymptotic stability conditions for both the instantaneous and convolutive methods to converge.

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