期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 58, 期 8, 页码 4064-4078出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2010.2048210
关键词
Adaptive filters; affine combination; least mean-square methods; tracking; transient analysis; unsupervised learning
资金
- FAPESP [2008/00773-1, 2008/04828-5]
- CNPq [302633/2008-1, 303361/2004-2]
In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.
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