Nonlinear system identification using IIR Spline Adaptive Filters

被引：40

作者：

Scarpiniti, Michele ^{[1
]}

Comminiello, Danilo ^{[1
]}

Parisi, Raffaele ^{[1
]}

Uncini, Aurelio ^{[1
]}

机构：

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

来源：

SIGNAL PROCESSING | 2015年 / 108卷

关键词：

Nonlinear adaptive filter; Spline adaptive filter; Wiener system identification; Spline interpolation; Least mean square;

D O I：

10.1016/j.sigpro.2014.08.045

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：

The aim of this paper is to extend our previous work on a novel and recent class of nonlinear filters called Spline Adaptive Filters (SAFs), implementing the linear part of the Wiener architecture with an IIR filter instead of an FIR one. The new learning algorithm is derived by an LMS approach and a bound on the choice of the learning rate is also proposed. Some experimental results show the effectiveness of the proposed idea. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：30 / 35

页数：6

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