In this paper, a new algorithm is proposed for the design of sparse FIR filters. Traditional l 1 -optimization-based methods take all the coefficients into l 1 -norm minimization. However, it is unnecessary since some of them can only take nonzero values to satisfy design specifications. Furthermore, minimizing l 1 norm of all the coefficients could drive the design results to deviate from the optimal ones. The proposed algorithm aims to identify nonzero coefficients at some crucial positions in each iteration to minimize the number of nonzero coefficients. Simulation results demonstrate that the proposed algorithm can achieve better design results than traditional l 1 -optimization methods.
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Sparse FIR filter design via partial L1 optimization
