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An L1-norm linearly constrained LMS algorithm applied to adaptive beamforming

de Andrade, J. F. ; de Campos, M. L. R. ; Apolinario, J. A.

2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012, p.429-432

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Título:
An L1-norm linearly constrained LMS algorithm applied to adaptive beamforming
Autor: de Andrade, J. F. ; de Campos, M. L. R. ; Apolinario, J. A.
Assuntos: Array signal processing ; Arrays ; Azimuth ; Convergence ; Heuristic algorithms ; Signal processing algorithms ; Vectors
É parte de: 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012, p.429-432
Descrição: We propose in this work an L 1 -norm Linearly-Constrained Least-Mean-Square (L 1 -CLMS) algorithm. In addition to the linear constraints present in the CLMS algorithm, the L 1 -CLMS algorithm takes into account an L 1 -norm penalty on the filter coefficients. The performance of the L 1 -CLMS algorithm is evaluated for a time-varying system identification under Gaussian noise and for an adaptive beamforming scenario. The effectiveness of the L 1 -CLMS algorithm is demonstrated by comparing, via computer simulations, its results with the CLMS algorithm. When employed in a sensor array, the L 1 -norm constraint increases the convergence rate making the proposed algorithm a good candidate for adaptive beamforming applications.
Editor: IEEE
Idioma: Inglês

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