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An algorithm based on non-squared sum of the errors
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DOI：10.1016/j.sigpro.2015.03.012.png)
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Abstract
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In adaptive filtering, several algorithms are developed in the quest for greater convergence speed, mostly relying on second order statistics. Here we modify the Recursive Least Square (RLS) equations by using as performance surface a weighted sum of even error power. As a result, the equations turn out to be simple, elegant, while yielding faster convergence and preserving the computational cost when compared with the existing RLS algorithm. (C) 2015 Published by Elsevier B.V.
Keywords:
RLS
Adaptive filtering
Non-quadratic function
Convergence speed
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