基于自适应模糊神经网络的噪声抵消器

本文讨论了基于自适应模糊神经网络的噪声抵消器的设计方法。自适应模糊神经网络系统具有非线性映射和自学习能力，能够用于噪声信号的非线性建模。它不仅能够获取信号的*佳估计，并且能够克服信号处理中存在的模型和噪声的不确定性、不完备性。该法设计的滤波器效果良好，并可以用于多路信号和复杂信号的噪声消除。  Adaptive Noise Cancellation Using Adaptive Fuzzy Neural Networks Algorithm

Lun Shuxian 1,2 ,Zhang Huaguang 1, Li Yingshun 1,3 , Feng jian 1

(1 Institute of Electric Automation ,Northeastern University ,Shenyang 110004 ,China; 2. Department of Information Science & Engineering,Jinzhou Teachers’ college,Jinzhou,China 121003; 3. Institute of Engineering , Shenyang Universty of Technology ,Shenyang 111003 , China )

Abstract : The Adaptive Fuzzy Neural Network Is employed for adaptive noise cancellation.Adaptive network-based fuzzy Inference system (ANFIS) not nonlinear mapping but also has the ability of self-learning.So ANFIS can be used to achieve the linear model of noise.Themethod not only achives the H2 optimal recontruction but also possesses a desired robust against the effect of uncertainties and Incomplete Information In signal processing. Simulation results show that the design methed can obtain a better sigal reconstruction performance and can be used In muiti-sensor signal and complicated signal processing.

Key words: Adaptive Noise Cancellation; Adaptive Filter; Fuzzy Neural Network