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Proportionate adaptive algorithm for nonsparse systems based on Krylov subspace and constrained optimization

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2 Author(s)
Yukawa, M. ; Brain Sci. Inst., RIKEN, Tokyo ; Utschick, W.

In this paper, we propose an efficient design of proportionality factors in the recently established algorithm named Krylov-proportionate normalized least mean-square (KPNLMS), which is an extention of the PNLMS algorithm to nonsparse (or dispersive) unknown systems by means of a Krylov subspace. The designing task takes a form of minimizing the number of iterations that is needed for an upper bound of the system mismatch to reach a specified target value. The minimization is performed under several constraints related to numerical stability, computational requirements, and nonnegativity, and its closed-form solution is derived. Numerical examples demonstrate that the proposed design significantly reduces the number of iterations needed to achieve target values of system mismatch especially when a low level of system mismatch is required.

Published in:

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Date of Conference:

19-24 April 2009