Modified Volterra LMS algorithm to fractional order for identification of Hammerstein non-linear system

被引：24
作者：
Chaudhary, Naveed Ishtiaq [1 ]
Aslam, Muhammad Saeed [2 ]
Raja, Muhammad Asif Zahoor [3 ]
机构：
[1] Int Islamic Univ, Dept Elect Engn, Islamabad, Pakistan
[2] Pakistan Inst Engn & Appl Sci, Dept Elect Engn, Islamabad, Pakistan
[3] COMSATS Inst Informat Technol, Dept Elect Engn, Attock Campus, Attock, Pakistan
来源：
IET SIGNAL PROCESSING | 2017年 / 11卷 / 08期
关键词：
nonlinear filters; least mean squares methods; adaptive signal processing; Volterra LMS algorithm; fractional order; Hammerstein nonlinear system identification; nonlinear recursive mechanism; VLMS approach; nonlinear Hammerstein Box-Jenkins system; statistical analyses; Nash-Sutcliffe efficiency; PARTICLE SWARM OPTIMIZATION; PARAMETER-ESTIMATION; ADAPTIVE STRATEGY; AUXILIARY-MODEL; GUEST EDITORIAL; DESIGN; FILTERS;
D O I：
10.1049/iet-spr.2016.0578
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this study, a new non-linear recursive mechanism for Volterra least mean square (VLMS) algorithm is proposed in the domain of non-linear adaptive signal processing and control. The proposed adaptive scheme is developed by applying concepts and theories of fractional calculus in weight adaptation structure of standard VLMS approach. The design scheme based on fractional VLMS (F-VLMS) algorithm is applied to parameter estimation problem of non-linear Hammerstein Box-Jenkins system for different noise and step size variations. The adaptive variables of F-VLMS are compared from actual parameters of the system as well as with the results of conventional VLMS for each case to verify its correctness. Comprehensive statistical analyses are conducted based on sufficient large number of independent runs and performance indices in terms of mean square error, variance account for and Nash-Sutcliffe efficiency establish the worth and effectiveness of the scheme.
引用
收藏
页码：975 / 985
页数：11
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