Iterative reweighted l1 design of sparse FIR filters

Authors:
Cristian Rusu;Bogdan Dumitrescu
Affiliations:
Department of Automatic Control and Computers, "Politehnica" University of Bucharest, Spl. Independenei 313, Bucharest 060042, Romania;Department of Automatic Control and Computers, "Politehnica" University of Bucharest, Spl. Independenei 313, Bucharest 060042, Romania and Tampere International Center for Signal Processing, Tampe ...
Venue:
Signal Processing
Year:
2012

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Abstract

Sparse FIR filters have lower implementation complexity than full filters, while keeping a good performance level. This paper describes a new method for designing 1D and 2D sparse filters in the minimax sense using a mixture of reweighted l"1 minimization and greedy iterations. The combination proves to be quite efficient; after the reweighted l"1 minimization stage introduces zero coefficients in bulk, a small number of greedy iterations serve to eliminate a few extra coefficients. Experimental results and a comparison with the latest methods show that the proposed method performs very well both in the running speed and in the quality of the solutions obtained.