对“用于自适应信道均衡的复数LMS和NLMS算法的分数阶变体设计”一文的评论
Comments on "Design of fractional-order variants of complex LMS and NLMS algorithms for adaptive channel equalization"
摘要：
本说明的目的是讨论最近提出的分数阶变量的复杂最小均方（CLMS）和归一化最小均方（NLMS）算法的一些方面，在“设计分数阶变量的复杂LMS和归一化LMS算法自适应信道滤波”[非线性动态。88（2），839-858（2017）]。据观察，这些算法并不总是收敛，而他们显然没有优势CLMS和NLMS算法，每当他们收敛。我们的主张是基于分析推理和支持的数值模拟。
英文摘要：
The purpose of this note is to discuss some aspects of recently proposed fractional-order variants of complex least mean square (CLMS) and normalized least mean square (NLMS) algorithms in ``Design of Fractional-order Variants of Complex LMS and Normalized LMS Algorithms for Adaptive Channel Equalization'' [Nonlinear Dyn. 88(2), 839-858 (2017)]. It is observed that these algorithms do not always converge whereas they have apparently no advantage over the CLMS and NLMS algorithms whenever they converge. Our claims are based on analytical reasoning and are supported by numerical simulations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
