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A swarm intelligence approach to the synthesis of two-dimensional IIR filters

机译:群智能方法合成二维IIR滤波器

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The concept of particle swarms, although initially introduced for simulating human social behaviors, has become very popular these days as an efficient means for intelligent search and optimization. The particle swarm optimization (PSO), as it is called now, does not require any gradient information of the function to be optimized, uses only primitive mathematical operators and is conceptually very simple. This paper investigates a novel approach to the designing of two-dimensional zero phase infinite impulse response (IIR) digital filters using the PSO algorithm. The design task is reformulated as a constrained minimization problem and is solved by a modified PSO algorithm. Numerical results are presented. The paper also demonstrates the superiority of the proposed design method by comparing it with two recently published filter design methods and two other state of the art optimization techniques.
机译:粒子群的概念虽然最初是为了模拟人类的社会行为而引入的,但如今已作为一种智能搜索和优化的有效手段而变得非常流行。现在称为粒子群优化(PSO),不需要优化函数的任何梯度信息,仅使用原始数学运算符,并且从概念上讲非常简单。本文研究了一种使用PSO算法设计二维零相位无限冲激响应(IIR)数字滤波器的新颖方法。将设计任务重新表述为约束最小化问题,并通过改进的PSO算法解决。给出了数值结果。本文还通过将其与最近发布的两种滤波器设计方法和其他两种最先进的优化技术进行比较,证明了该设计方法的优越性。

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