On the selection of optimal nonlinearities for stochastic gradient adaptive algorithms

This paper derives an expression for the optimal error nonlinearity in adaptive filter design. Using an energy conservation relation, and some typical assumptions, the choice of the error function is optimized by minimizing the mean-square deviation subject to a fixed rate of convergence. The resulting optimal choice is shown to subsume earlier results as special cases.

Published in:
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP, 1, 464-467
Presented at:
IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP, Istanbul, Turkey, June 5-9, 2000

 Record created 2017-12-19, last modified 2018-09-13

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