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Robust adaptive filtering algorithms for α-stable random processes

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3 Author(s)
Aydin, G. ; Dept. of Electr. Eng., Bilkent Univ., Ankara, Turkey ; Arikan, O. ; Cetin, A.E.

A new class of algorithms based on the fractional lower order statistics is proposed for finite impulse response adaptive filtering in the presence of a stable processes. It is shown that the normalized least mean p-norm (NLMP) and Douglas' family of normalized least mean square algorithms are special cases of the proposed class of algorithms. A convergence proof for the new algorithm is given by showing that it performs a descent-type update of the NLMP cost function. Simulation studies indicate that the proposed algorithms provide superior performance in impulsive noise environments compared to the existing approaches

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Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on  (Volume:46 ,  Issue: 2 )