Novel Stochastic Gradient Adaptive Algorithm with Variable Length
نویسندگان
چکیده
The goal of this paper is to present a novel variable length LMS (Least Mean Square) algorithm, in which the length of the adaptive filter is always a power of two and it is modified using an error estimate. Unlike former variable length stochastic gradient adaptive techniques, the proposed algorithm works in non-stationary situations. The implementation of the adaptive filter is described and results of computer simulations are provided.
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