Optimal expansions of Meixner-like model

Safa Maraoui, A. Krifa, Kais Bouzrara
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Abstract

This article focuses on modeling and identification of a LTI system represented by Meixner-like functions. However a significant reduction of this model is subject to an optimal choice of Meixner-like pole. An iterative algorithm based on the Newton-Raphson's approximation technique and evolutionary method are proposed for the optimization of the Meixner-like pole from input/output measurements. The effectiveness of this method is tested on numerical example.
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类meixner模型的最优展开
本文主要讨论由类迈克斯纳函数表示的LTI系统的建模和识别。然而,该模型的显着减小取决于米克斯纳极点的最佳选择。提出了一种基于牛顿-拉夫森近似技术和进化方法的迭代算法,用于从输入/输出测量中优化类迈克斯纳极点。通过数值算例验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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