Almost sure convergence of a decreasing gain sign algorithm for adaptive filtering

The convergence analysis of a sign algorithm with decreasing gain, when governing the weights of an adaptive filter, is presented. The analysis is done in a noiseless case. A rigorous proof of almost-sure convergence to the optimal filter is attained under a weak-ergodicity assumption that includes the case, important in practice, of correlated observations.<
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