A Crest-Factor Optimization Algorithm for Multisine Signals based on the Evolutionary Role Playing Game Theory

Ahmed Yahia Kallel, O. Kanoun
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引用次数: 1

Abstract

In impedance spectroscopy, excitation signals should be limited in their amplitude to fulfil the linearity condition and in their duration to fulfill the stability condition. Multisine excitation signals are suitable because they can reduce the excitation time duration, but they need to be optimized concerning crest factor (CF). A higher challenge is the optimization of the crest factor of multisine signals. In this paper, we propose a hybrid deterministic-heuristic optimization method for CF optimization based on the Evolutionary Role Playing Game Theory able to realize multisine signals with lower and more consistent CF for logarithmically distributed signal frequency components. The novel optimization method needs a short execution time, which is comparable to that of deterministic methods. The method validation has been carried out for bioimpedance measurement. In the case of bioimpedance measurement, the new method reaches a CF with a median of 1.76, which is significantly lower than state-of-the-art methods realizing a CF typically between 1.89 and 2.79.
基于进化角色扮演博弈论的多正弦信号波峰因子优化算法
在阻抗谱中,为了满足线性条件,必须限制激励信号的幅值;为了满足稳定条件,必须限制激励信号的持续时间。多正弦激励信号可以缩短激励时间,但需要对其进行波峰因子(CF)优化。一个更高的挑战是多正弦信号的波峰因子的优化。在本文中,我们提出了一种基于进化角色扮演博弈论的混合确定性-启发式优化方法,该方法能够实现对数分布的信号频率成分具有更低且更一致的CF的多正弦信号。该优化方法的执行时间短,与确定性方法相当。该方法已在生物阻抗测量中进行了验证。在生物阻抗测量中,新方法的CF值中值为1.76,明显低于目前最先进的方法,其CF值通常在1.89至2.79之间。
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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