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Cultural firework algorithm and its application for digital filters design

机译:文化烟花算法及其在数字滤波器设计中的应用

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摘要

The substance of the digital filter design is a multi-parameter optimisation problem. This paper presents a joint objective function to design finite impulse response (FIR) digital filters and infinite impulse response (IIR) digital filters, and a cultural firework (CF) algorithm is proposed to implement filter designs. The design of the filter is transformed into the constrained optimisation problem, and the cultural firework algorithm is used to search optimal value of filter design parameters in the parameter space with parallel search. The proposed cultural firework algorithm is a multi-dimensional search algorithm for optimisation of real numbers, which uses mechanisms of cultural evolution to update the locations of cultural sparks. Computer simulations have showed that FIR and IIR digital filters based on the CF algorithm are superior to previous filters based on particle swarm optimisation (PSO), quantum-behaved particle swarm optimisation (QPSO) and adaptive quantum-behaved particle swarm optimisation (AQPSO) in the convergence speed and optimisation results. The effectiveness and superiority of the CF are also demonstrated by computer simulations.
机译:数字滤波器设计的实质是一个多参数优化问题。本文提出了一个联合目标函数来设计有限冲激响应(FIR)数字滤波器和无限冲激响应(IIR)数字滤波器,并提出了一种文化烟花(CF)算法来实现滤波器设计。将滤波器的设计转化为约束优化问题,采用文化烟花算法通过并行搜索在参数空间中搜索滤波器设计参数的最优值。所提出的文化烟花算法是用于优化实数的多维搜索算法,该算法使用文化进化机制来更新文化火花的位置。计算机仿真表明,基于CF算法的FIR和IIR数字滤波器优于以前的基于粒子群优化(PSO),量子行为粒子群优化(QPSO)和自适应量子行为粒子群优化(AQPSO)的滤波器。收敛速度和优化结果。 CF的有效性和优越性也通过计算机仿真得到了证明。

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