复杂系统辨识的分数阶复LMS算法

Jawwad Ahmad, Shujaat Khan, Muhammad Usman, I. Naseem, M. Moinuddin, Hassan Jamil Syed
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引用次数: 15

摘要

本文提出了一种基于分数阶微积分的复杂系统辨识最小均方算法。本文提出的分数阶复数最小均方(FCLMS)算法成功地解决了分数阶复数最小均方算法中由于负权重或复杂输入/输出引起的复杂误差问题。为了评估的目的,考虑了一个复杂的线性系统。FCLMS算法在不影响稳态误差的情况下,成功地识别了复杂系统,取得了较高的收敛速度。该方法的收敛速度是复最小均方法(CLMS)的2倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FCLMS: Fractional complex LMS algorithm for complex system identification
In this paper, a fractional order calculus based least mean square algorithm is proposed for complex system identification. The proposed algorithm, named as, fractional complex least mean square (FCLMS), successfully deals with the problem of complex error due to negative weights or complex input/output in the FLMS. For the evaluation purpose a complex linear system is considered. The FCLMS algorithm successfully identifies the complex system and achieve high convergence rate without compromising the steady state error. The convergence rate of the proposed FCLMS is two times better than that of the complex least mean square (CLMS).
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