Set-Membership Proportionate Affine Projection Algorithms

Autor: Apolinário José A, Diniz Paulo SR, Werner Stefan
Jazyk: angličtina
Rok vydání: 2007
Předmět:
Zdroj: EURASIP Journal on Audio, Speech, and Music Processing, Vol 2007, Iss 1, p 034242 (2007)
Druh dokumentu: article
ISSN: 1687-4714
1687-4722
Popis: Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. In this paper, the idea of proportionate adaptation is combined with the framework of set-membership filtering (SMF) in an attempt to derive novel computationally efficient algorithms. The resulting algorithms attain an attractive faster converge for both situations of sparse and dispersive channels while decreasing the average computational complexity due to the data discerning feature of the SMF approach. In addition, we propose a rule that allows us to automatically adjust the number of past data pairs employed in the update. This leads to a set-membership proportionate affine projection algorithm (SM-PAPA) having a variable data-reuse factor allowing a significant reduction in the overall complexity when compared with a fixed data-reuse factor. Reduced-complexity implementations of the proposed algorithms are also considered that reduce the dimensions of the matrix inversions involved in the update. Simulations show good results in terms of reduced number of updates, speed of convergence, and final mean-squared error.
Databáze: Directory of Open Access Journals
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