Adaptive signal processing
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Adaptive Filters: Theory and Applications
Adaptive Filters: Theory and Applications
Convergence analysis of sign-sign LMS algorithm for adaptive filters with correlated Gaussian data
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
Comparative tracking performance of the LMS and RLS algorithms forchirped narrowband signal recovery
IEEE Transactions on Signal Processing
Performance of LMS-based adaptive filters in tracking atime-varying plant
IEEE Transactions on Signal Processing
Analysis of stability and performance of adaptation algorithms with time-invariant gains
IEEE Transactions on Signal Processing
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
EURASIP Journal on Advances in Signal Processing
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A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,-1) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.