Digital stable IIR high pass filter optimization using PSO-CFIWA

S. Saha, Sonam Yangchen, D. Mandal, R. Kar, S. Ghoshal
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引用次数: 2

Abstract

In this paper, an optimal design of stable digital high pass infinite impulse response (IIR) filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA) has been presented. The conventional gradient based optimization techniques are not efficient enough for handling digital IIR filter design due to the sub-optimality problem. The proposed optimization technique PSO-CFIWA is a heuristic search algorithm and capable enough to handle non differentiable optimization problem to find optimal solution in multidimensional search space. Performance of the proposed algorithm is compared with well accepted evolutionary algorithms such as particle swarm optimization (PSO) and real coded genetic algorithm (RGA). From the simulation study it is established that the PSO-CFIWA outperforms RGA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality i.e. the stop band attenuation, transition width, pass band and stop band ripples. Further, the pole-zero analysis justifies the stability of the designed optimized IIR filter.
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基于PSO-CFIWA的数字稳定IIR高通滤波器优化
提出了一种基于收缩因子和惯性权值的粒子群优化算法(PSO-CFIWA)的稳定型数字高通无限脉冲响应滤波器的优化设计方法。传统的基于梯度的优化技术由于次优性问题而无法有效地处理数字IIR滤波器设计。所提出的优化技术PSO-CFIWA是一种启发式搜索算法,能够处理多维搜索空间中求最优解的不可微优化问题。将该算法的性能与粒子群优化算法(PSO)和实编码遗传算法(RGA)进行了比较。仿真研究表明,PSO- cfiwa不仅在设计滤波器的精度上优于RGA和PSO,而且在收敛速度和解的质量(即阻带衰减、过渡宽度、通带和阻带波纹)方面也优于PSO。此外,极点-零点分析验证了优化后的IIR滤波器的稳定性。
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