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根据FIR滤波器幅频响应特性,采用分组并行粒子群算法计算滤波器的系数,在粒子搜索过程中进行分组和并行化处理,以防止算法出现早熟同时又能提高算法的收敛速度。该算法搜索的滤波器系数,能使FIR滤波器幅频响应与理想幅频响应之间的均方误差最小。文章以低通滤波器设计为例进行了仿真,从仿真结果可以看出,分组并行粒子群优化算法设计的FIR滤波器具有运算量小、速度快和性能好等优点。
According to the amplitude-frequency response characteristics of FIR filter, the parallel PSO algorithm is used to calculate the coefficients of the filter, which are grouped and parallelized in the particle search process to prevent the premature convergence and improve the convergence speed of the algorithm. The filter coefficients searched by this algorithm can minimize the mean square error between the FIR filter amplitude-frequency response and the ideal amplitude-frequency response. The article takes the low-pass filter design as an example. The simulation results show that the FIR filter designed by parallel PSO algorithm has the advantages of low computational complexity, high speed and good performance.