基于径向基函数网络的水声信号预测模型研究  

Research on Prediction Model of Underwater Acoustic Signals Based on Radial Basis Function Neural Network

作　　者：王红萍[1] 金彦丰[1] 曹海军[1] 陈晓辉[1] 

机构地区：[1]91388部队

出　　处：《舰船电子工程》2008年第10期170-173,190,共5页Ship Electronic Engineering

摘　　要：随着舰船隐身降噪技术的不断发展,舰船辐射噪声信号检测变得愈加困难。针对这种情况,将RBF神经网络引入到水声信号的预测中,建立水声信号的全局预测模型。通过对Henon和Lorenz映射仿真,验证了RBF预测模型的有效性。运用全局预测模型对两种实际水声信号进行预测。实验证明,该预测模型学习速度快,所需样本点少,效果较准确,在水声信号检测中具有良好的发展前景。With the development of ship s noise reduction technology,the detection of ship radiated signals has become more and more difficult.Considering about the point,The principium of radial basis function(RBF) neural network is introduced into the prediction of underwater acoustic signals,and a prediction model of underwater acoustic signals is proposed.A simulation test of the Henon and Lorenz is given to show validity of the model.Finally,we use this model to predict two actual underwater acoustic signals.The ...

关 键 词：径向基函数网络 预测模型 水声信号 仿真 

分 类 号：U666.7[交通运输工程—船舶及航道工程]