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Digital stable IIR high pass filter optimization using PSO-CFIWA

机译:使用PSO-CFIWA的数字稳定IIR高通滤波器优化

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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.
机译:本文提出了一种采用收缩因子和惯性权重法的粒子群算法(PSO-CFIWA)的稳定数字高通无限冲激响应(IIR)滤波器的优化设计。由于次优问题,传统的基于梯度的优化技术不足以处理数字IIR滤波器设计。提出的优化技术PSO-CFIWA是一种启发式搜索算法,具有足够的能力来处理不可微的优化问题,从而在多维搜索空间中找到最优解。将该算法的性能与公认的进化算法(例如粒子群优化(PSO)和实数编码遗传算法(RGA))进行了比较。通过仿真研究可以确定,PSO-CFIWA不仅在设计滤波器的精度方面,而且在收敛速度和解决方案质量(即阻带衰减,过渡宽度,通带和阻带波纹)方面均优于RGA和PSO。 。此外,零极点分析证明了设计的优化IIR滤波器的稳定性。

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