基于RBF网络的有源噪声控制

提出一种神经自适应噪声有源控制（ANC）的方法。应用RBF（Radial Basis Function)网络对噪声进行有源控制。针对RBF的网络特点,使用递阶遗传算法确定网络参数（连接权、隐节点中心和宽度），同时解决了网络拓扑结构的优化训练。利用RBF网络的有源噪声控制系统用于三维空间传播的宽频带空调噪声的降噪获得了良好的效果。

A Study of Active Noise Control Based on RBF Neural Networks

In this paper, a method of neuro-adaptive active nois e control (ANC) system is presented. The RBF(Radial Basis Function)is consider ed both in the modeling and control context. A hierarchical genetic algorithm fo r RBF neural networks is used to determine network parameters such as centers, w idths and connection weights. The configuration of RBF network is also establis hed at the same time during training. A feed-forward ANC system is used to can cel broadband air-condition noise in a three-dimensional propagation medium. T he developed neuro-adaptive ANC algorithm is implemented within a free-field e nvironment, and simulation results to verify its performance are presented and d iscussed.