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An optimized EASI algorithm
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DOI：10.1016/j.sigpro.2008.08.015.png)
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This paper addresses the problem of blind source separation and presents a kind of optimized equivariant adaptive separation via independence (EASI) algorithms. According to the cumulant based approximation to the mutual information contrast function, the EASI learning rule is optimized by multiplying the symmetric part with an optimal time variant weight coefficient. Simulation results show the proposed optimized EASI algorithms outperform the existing algorithms in convergent speed and steady-state accuracy. (C) 2008 Elsevier B.V. All rights reserved.
Keyword:
Blind source separation
Cumulant based approximation of contrast function
EASI algorithm
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