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ADAPTIVE SIGNAL PROCESSING THROUGH STOCHASTIC APPROXIMATION*
- Source: Geophysical Prospecting, Volume 19, Issue 4, Apr 1971, p. 718 - 728
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- 27 Apr 2006
Abstract
One of the problems in signal processing is estimating the impulse response function of an unknown system. The well‐known Wiener filter theory has been a powerful method in attacking this problem. In comparison, the use of stochastic approximation method as an adaptive signal processor is relatively new. This adaptive scheme can often be described by a recursive equation in which the estimated impulse response parameters are adjusted according to the gradient of a predetermined error function.
This paper illustrates by means of simple examples the application of stochastic approximation method as a single‐channel adaptive processor. Under some conditions the expected value of its weight sequence converges to the corresponding Wiener optimum filter when the least‐mean‐square error criterion is used.