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A novel adaptive leakage factor scheme for enhancement of a variable tap-length learning algorithm.

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conference contribution
posted on 04.12.2009 by Leilei Li, Jonathon Chambers
In this paper a new adaptive leakage factor variable tap-length learning algorithm is proposed. Through analysis the converged difference between the segmented mean square error (MSE) of a filter formed from a number of the initial coefficients of an adaptive filter, and the MSE of the full adaptive filter, is confirmed as a function of the tap-length of the adaptive filter to be monotonically non-increasing. This analysis also provides a systematic way to select the key parameters in the fractional tap-length (FT) learning algorithm, first proposed by Gong and Cowan, to ensure convergence to permit calculation of the true tap-length of the unknown system and motivates the need for adaptation in the leakage factor during learning. A new strategy for adaptation of the leakage factor is therefore developed to satisfy these requirements with both small and large initial tap-length. Simulation results are presented which confirm the advantages of the proposed scheme over the original FT scheme.



  • Mechanical, Electrical and Manufacturing Engineering


LI, L., and CHAMBERS, J.A., 2008. A novel adaptive leakage factor scheme for enhancement of a variable tap-length learning algorithm. IN: Proceedings of 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), Las Vegas, Nevada, 31 March-4 April, pp. 3837-3840.




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