کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
564013 | 875555 | 2013 | 12 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: On the performance of adaptive pruned Volterra filters On the performance of adaptive pruned Volterra filters](/preview/png/564013.png)
Because of the high computational burden required by adaptive Volterra filters, several of their practical implementations consider some type of sparseness for complexity reduction. Such implementations are obtained using application-oriented strategies to prune a standard Volterra filter by zeroing some of its coefficients. In this context, the main challenge is to choose a pruning strategy that leads to minimum loss of performance. Meeting this challenge is not a trivial task because of the variety of strategies available for obtaining pruned Volterra filters as well as due to the lack of a theoretical framework describing these strategies in a general scenario. Thus, the primary objective of this research work is to establish a basis for assessing adaptive pruned Volterra filters. For such, a unifying scheme describing the input vectors of different pruned Volterra implementations is proposed along with an extended version of a constrained approach used to represent sparseness in adaptive filters. Based on this foundation, an analysis of the performance of adaptive pruned Volterra filters in terms of the minimum mean-square error is carried out. Simulation results are presented attesting the effectiveness of the proposed approach.
► A new foundation for the analysis of adaptive pruned Volterra filters is proposed.
► The different pruned Volterra filters are described using a novel unifying scheme.
► An extension of a constrained approach for analyzing adaptive filters is introduced.
► A minimum mean-square-error analysis is performed based on the proposed foundation.
► Results of numerical simulation attest the effectiveness of the presented theory.
Journal: Signal Processing - Volume 93, Issue 7, July 2013, Pages 1909–1920