Sparse FIR filter design based on Genetic Algorithm

Heng Zhao, Wen Bin Ye, Ya Jun Yu

Abstract: Sparse patterns for digital filters have been suggested to reduce the computational cost. However, the minimization of the number of non-zero coefficients under required filter order and frequency domain constraints is difficult to be accomplished in polynomial time in many cases. In this paper, a two-stage design based on Genetic Algorithm (GA) is proposed to search for the optimal solution with a given specification. A preliminary optimization stage is introduced to enhance the efficiency of the proposed GA. The proposed algorithm is evaluated through two sets of examples, which generate better results than existing algorithms.