A novel adaptive leakage factor scheme for enhancement of a variable tap-length learning algorithm.
conference contributionposted on 04.12.2009 by Leilei Li, Jonathon Chambers
Any type of content contributed to an academic conference, such as papers, presentations, lectures or proceedings.
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