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Improved minimax optimisation algorithms and their application in the design of recursive digital filters

机译:改进的极大极小优化算法及其在递归数字滤波器设计中的应用

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摘要

A technique that can improve the performance of available optimisation algorithms, in applications where the objective function involves the sampling of a function with respect to an independent variable, is proposed. The technique is then applied in conjunction with two well known minimax algorithms for the design of recursive digital filters. Extensive experimental results show that the new technique reduces the approximation errors significantly and eliminates the problem of spikes in the error function. Although the amount of computation needed to carry out a design for a fixed density of grid points is increased somewhat, improved robustness is achieved, which allows a reduced density of grid points and eliminates waste of computational effort in unsuccessful designs.
机译:提出了一种在目标函数涉及针对自变量的函数采样的应用中,可以提高可用优化算法性能的技术。然后,将该技术与两个众所周知的minimax算法结合使用,以设计递归数字滤波器。大量的实验结果表明,该新技术显着降低了近似误差,并消除了误差函数中的尖峰问题。尽管为固定密度的网格点进行设计所需的计算量有所增加,但仍实现了更高的鲁棒性,这可以降低网格点的密度并消除了不成功设计中的计算量浪费。

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