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基于RBF神经网络的非线性滤波器研究

发表时间:2011-11-30  浏览量:1250  下载量:340
全部作者: 陈美玲,冀常鹏
作者单位: 辽宁工程技术大学研究生学院;辽宁工程技术大学电子与信息工程学院
摘 要: 针对数字滤波器不能对滤波器的权系数进行实时计算,不能实现实时非线性滤波等问题,提出一种非线性滤波方法,即利用径向基函数(radial basis function,RBF)网络唯一具有的精确局部逼近特性,将其应用到非线性滤波。通过Matlab软件进行网络的设计与误差分析可知,将RBF网络运用到非线性滤波是可行的,而且效果较好。该方法弥补了线性滤波器对非线性干扰的处理缺陷,改进了以往的滤波技术。
关 键 词: 信号与信息处理;数字滤波器;径向基函数;非线性滤波;信号处理
Title: Research on nonlinear filter based on RBF neural network
Author: CHEN Meiling, JI Changpeng
Organization: Graduate College, Liaoning Technical University; School of Electronics and Information Engineering, Liaoning Technical University
Abstract: Digital filter has many problems such as can not calculate weighting coefficients of filter in real time and can not achieve real-time nonlinear filtering. In order to solve these problems, a nonlinear filtering method which utilizes local approximation properties of radial basis function (RBF) is proposed in this paper, and is applied to nonlinear filtering. Through Matlab network design and error analysis, it is concluded that the application of RBF to nonlinear filtering is feasible and has a better result. The method can make up the processing defect of linear filter when dealing with the nonlinear interference and improve previous filtering technology.
Key words: signal and information processing; digital filter; radial basis function; non-linear filter; signal processing
发表期数: 2011年11月第22期
引用格式: 陈美玲,冀常鹏. 基于RBF神经网络的非线性滤波器研究[J]. 中国科技论文在线精品论文,2011,4(22):2068-2071.
 
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