Design of Hybrid Nonlinear Spline Adaptive Filters for Active Noise Control

被引：0

作者：

Patel, Vinal ^{[1
]}

Comminiello, Danilo ^{[2
]}

Scarpiniti, Michele ^{[2
]}

George, Nithin V. ^{[1
]}

Uncini, Aurelio ^{[2
]}

机构：

[1] Indian Inst Technol Gandhinagar, Dept Elect Engn, Gandhinagar, Gujarat, India

[2] Sapienza Univ Rome, Dept Informat Engn Elect & Telecommun DIET, I-00184 Rome, Italy

来源：

2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2016年

关键词：

ACOUSTIC ECHO CANCELLATION; SYSTEM-IDENTIFICATION; CONVERGENCE PROPERTIES; NEURAL NETWORKS; ALGORITHMS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we focus on the problem of removing noise in the acoustic domain. To this end, we introduce a class of hybrid nonlinear spline filters, which are designed as a cascade of an adaptive spline function and a single layer adaptive nonlinear network. The adaptive nonlinear networks employed in this work are the functional link network and the even mirror Fourier nonlinear network. Suitable update rules, which not only update the adaptive weights of the nonlinear networks, but also introduce adaptability in the developed spline function are derived. The proposed nonlinear filters have been successfully applied to nonlinear system identification as well as nonlinear active noise control. The new filters have been shown to outperform other popular nonlinear filters.

引用

页码：3420 / 3425

页数：6

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