Abstract
A new stochastic gradient algorithm for data echo cancellation, based on the cost function adaptation (CFA) is proposed. Qualities of the new adaptation algorithm as compared with that of the least mean square (LMS) and the least mean fourth (LMF) algorithms are demonstrated by means of simulations. Thus it is shown that continuous and automatic, adaptation of the error power yields a more satisfactory result. The cost function adaptation allows an increase in convergence rate and, at the same time, an improvement of residual error. The results were obtained with non-Gaussian binary sequences of data in presence of far-end signals in data echo-cancellers for full duplex digital data transmission over telephone lines.
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