Adaptive global best steered Cuckoo search algorithm for FIR filter design

P. Das, S. Naskar, S. N. Patra
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引用次数: 2

Abstract

In this paper, we propose design of even order low pass FIR filter and odd order bandpass FIR filter using coefficients optimized by an adaptive Global Best steered Cuckoo Search Algorithm (gbest CSA). For optimization, we use a mean square error based cost function as the fitness function. We evaluated the efficacy of the proposed technique by comparing the filter responses with responses of the filters designed using standard Cuckoo Search Algorithm and traditional technique of filter design with Parks McClellan algorithm. Efficacy of the proposed algorithm compared to the conventional CSA is proved using seven standard benchmark functions.
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自适应全局最佳导向杜鹃搜索算法在FIR滤波器设计中的应用
本文提出了一种基于自适应全局最佳导向布谷鸟搜索算法(gbest CSA)优化系数的偶阶低通FIR滤波器和奇阶带通FIR滤波器的设计。为了优化,我们使用基于均方误差的成本函数作为适应度函数。通过将滤波器响应与标准布谷鸟搜索算法设计的滤波器响应和采用Parks McClellan算法的传统滤波器设计技术设计的滤波器响应进行比较,评估了该技术的有效性。用7个标准基准函数证明了该算法与传统CSA算法相比的有效性。
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