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 clippedlms, and uses a three-level quantization (+1, 0, -1) sche...
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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 clippedlms, 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 clippedlms (MClms) algorithm has better tracking than the lmsalgorithm. 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 MClmsalgorithm compared to the lmsalgorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
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