Combination of Adaptive Filters with Coefficients Feedback
arXiv (Cornell University)(2016)
摘要
In parallel combinations of adaptive filters, the component filters are usually run independently to be later on combined, leading to a stagnation phase before reaching a lower error. Conditional transfers of coefficients between the filters have been introduced in an attempt to address this issue. The present work proposes a more natural way of accelerating the convergence to steady-state, using a cyclic feedback of the overall weights to all component filters, instead of a unidirectional conditional transfer. It is shown that, depending on the cycle length, the resulting recursion is equivalent to either: (i) the independent combination, (ii) a variable step size adaptive filter, or (iii) a new hybrid algorithm. Comments on the universality of the approach are presented along with a technique to design the cycle length. Comparisons in stationary and non-stationary system identification scenarios demonstrate the superior performance of this new combination method.
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关键词
Convex combination,adaptive filters,coefficients feedback
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