粒子群和Levy飞行萤火虫自适应DSP算法的改进比较

W. Jenkins, Magni Hussain
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引用次数: 0

摘要

已有的研究结果表明,LFFA算法可以有效地应用于IIR自适应滤波器、非线性自适应滤波器、IIR耦合形式自适应滤波器和IIR格梯自适应滤波器。最近的研究表明,LFFA可以应用于自适应二维麦克莱伦“无约束”变换滤波器,因此自适应性可以近似频域轮廓。本文演示了如何对LFFA算法进行特殊的块长度修改,从而产生2-D Modified LFFA (2-D MLFFA),该算法在2D-MLFFA向全局最小MSE收敛时提高了自适应收敛速率并降低了MSE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modification Comparisons of the Particle Swarm and Levy Flight Firefly Adaptive DSP Algorithms
Previous research results have demonstrated that the bio-inspired Lévy Flight Firefly Algorithm (LFFA) can be effectively used in IIR adaptive filters, non-linear adaptive filters, IIR coupled form adaptive filters, and IIR lattice-ladder adaptive filters. It has recently been shown that the LFFA can be applied to adaptive 2-D McClellan "unconstrained" Transform filters so the adaptivity can approximate the frequency domain contours. This paper demonstrates how a special block length modification to the LFFA algorithm produces a 2-D Modified LFFA (2-D MLFFA) that enhances the adaptive convergence rate and lowers the MSE as the 2D-MLFFA converges toward the global minimum MSE.
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