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An ICA-based adaptive filter algorithm for system identification using a state space approach

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2 Author(s)
Jun-Mei Yang ; Grad. Sch. of Inf., Kyoto Univ., Kyoto ; Sakai, H.

This paper proposes a new ICA-based adaptive filter algorithm for system identification using a state space approach. An additive noise model is considered and the signal is separated from the noisy observation. First, we introduce an augmented state-space expression of the observed signal representing the problem in terms of ICA, and then using the natural gradient, we derive a new algorithm. The local convergence conditions of the proposed algorithm is derived. Some simulations are carried out to illustrate its effectiveness.

Published in:

Signal Processing, 2008. ICSP 2008. 9th International Conference on

Date of Conference:

26-29 Oct. 2008