Visible to the public Affine-Projection-Like Adaptive-Filtering Algorithms Using Gradient-Based Step Size

TitleAffine-Projection-Like Adaptive-Filtering Algorithms Using Gradient-Based Step Size
Publication TypeJournal Article
Year of Publication2014
AuthorsBhotto, M.Z.A., Antoniou, A.
JournalCircuits and Systems I: Regular Papers, IEEE Transactions on
Date PublishedJuly
Keywordsa posteriori error vector, acoustic-echo-cancelation applications, adaptive filters, adaptive-filtering algorithms, affine-projection algorithms, affine-projection-like adaptive-filtering algorithms, Algorithm design and analysis, channel-equalization, computational complexity, convergence, gradient methods, gradient-based step size, input signal matrix, Least squares approximations, Matrix decomposition, mean square error methods, mean-square error in adaptive filtering, mean-square-error analysis, Steady-state, steady-state misalignment, system-identification, Vectors

A new class of affine-projection-like (APL) adaptive-filtering algorithms is proposed. The new algorithms are obtained by eliminating the constraint of forcing the a posteriori error vector to zero in the affine-projection algorithm proposed by Ozeki and Umeda. In this way, direct or indirect inversion of the input signal matrix is not required and, consequently, the amount of computation required per iteration can be reduced. In addition, as demonstrated by extensive simulation results, the proposed algorithms offer reduced steady-state misalignment in system-identification, channel-equalization, and acoustic-echo-cancelation applications. A mean-square-error analysis of the proposed APL algorithms is also carried out and its accuracy is verified by using simulation results in a system-identification application.

Citation Key6747407