RBF网络在有源降噪系统中的应用仿真  

The Application Simulation of RBF Neural Network in Active Noise Control System

作　　者：姜丽飞[1] 

机构地区：[1]唐山师范学院,河北唐山063000

出　　处：《机床与液压》2011年第9期132-134,共3页Machine Tool & Hydraulics

基　　金：唐山师范学院科研基金资助项目(10D05)

摘　　要：针对车辆舱室内的噪声特点,在分析噪声系统非线性特性的基础上,将高速实时信号处理器DSP应用于有源降噪系统的硬件设计中,提出一种基于变结构RBF神经网络的噪声自适应控制方案,给出滤波-X算法并进行仿真验证。同时将该滤波算法的降噪效果和基本的滤波-X算法的进行比较。结果表明,采用该控制算法取得了良好的降噪效果。Aiming at the characteristics of noise in vehicle cabins,and analyzing nonlinear characteristics of the system,the high-speed real-time signal processor（DSP）was used in active noise control system and an adaptive noise control project based on RBF networks was proposed.An algorithm of FX-RBF was given and simulated.Its noise reduction effect was compared with that of the basic filter-X algorithm.Simulation results showed that the noise reduction effect of the FX-RBF algorithm is good.

关 键 词：有源噪声控制 RBF网络 滤波-X算法 MATLAB仿真 DSP 

分 类 号：TK411.6[动力工程及工程热物理—动力机械及工程]