Backtracking search integrated with sequential quadratic programming for nonlinear active noise control systems

被引：40

作者：

Khan, Wasim Ullah ^{[1
]}

Ye, ZhongFu ^{[1
]}

Chaudhary, Naveed Ishtiaq ^{[2
]}

Raja, Muhammad Asif Zahoor ^{[3
]}

机构：

[1] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Natl Engn Lab Speech & Language Informat Proc, Hefei 230026, Anhui, Peoples R China

[2] Int Islamic Univ, Dept Elect Engn, Islamabad, Pakistan

[3] COMSATS Inst Informat Technol, Dept Elect Engn, Attock, Pakistan

来源：

APPLIED SOFT COMPUTING | 2018年 / 73卷

关键词：

Active noise control; System identification; Backtracking search algorithm; Sequential quadratic programming; Hybrid computing; GENETIC ALGORITHM; OPTIMIZATION; CANCELLATION; DYNAMICS; ANALYZE; FLOW; FEEDFORWARD; FEEDBACK; MODEL; HEURISTICS;

D O I：

10.1016/j.asoc.2018.08.027

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the present work, integrated strength of backtracking search algorithm (BSA) and sequential quadratic programming (SQP) is exploited for nonlinear active noise control (ANC) systems. Legacy of approximation theory in mean squared sense is utilized to construct a cost function for ANC system based on finite impulse response (FIR) and Volterra filtering procedures. Global search efficacy of BSA aided with rapid local refinements with SQP is practiced for effective optimization of fitness function for ANC systems having sinusoidal, random and complex random signals under several variants based on linear/nonlinear and primary/secondary paths. Statistical observations demonstrated the worth of stochastic solvers BSA and BSA-SQP by means of accuracy, convergence and complexity indices. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：666 / 683

页数：18

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