Sliding-Window RLS Low-Cost Implementation of Proportionate Affine Projection Algorithms

Autor(es)

Zakharov, Yuriy ^[1] ; Nascimento, Vitor H. ^[2]

Afiliação do(s) autor(es)

^[1] Univ York, Dept Elect, York YO10 5DD, N Yorkshire - England

^[2] Univ Sao Paulo, Dept Elect Syst Engn, BR-05508970 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING; v. 22, n. 12, p. 1815-1824, DEC 2014.
• Citações Web of Science: 5

Resumo

This paper addresses adaptive filtering for sparse identification. Proportionate affine projection algorithms (PAPAs) are known to be efficient techniques for this purpose. We show that the PAPA performance may improve with an increase in the projection order M (for example, such as M = 512), which, however, also results in an increased complexity; the complexity is in general O((MN)-N-2) or at least O(MN) operations per sample, where N is the filter length. We show that PAPAs are equivalent to specific sliding-window recursive least squares (SRLS) adaptive algorithms with time-varying and tap-varying diagonal loading (SRLS-VDLs). We then propose an approximation to the SRLS-VDLs based on dichotomous coordinate descent (DCD) iterations with a complexity of O(NuN) which does not depend on M; it depends on the number of DCD iterations N-u, which as we show can be significantly smaller than M, thus allowing a low-complexity implementation of PAPA adaptive filters. (AU)

• Processo FAPESP: 11/06994-2 - Algoritmos de baixo custo computacional para processamento de sinais acústicos
• Beneficiário: Vitor Heloiz Nascimento
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 12/50565-1 - Adaptive compressive sensing-aware techniques: desinf algorithms and applications
• Beneficiário: Vitor Heloiz Nascimento
• Modalidade de apoio: Auxílio à Pesquisa - Regular