基于小波神经网络的数字信号调制方式识别  

Recognition of Digital Signal Modulation Mode Based on Wavelet Neural Network

作　　者：梁晔 郝洁[2] 石蕊 

机构地区：[1]兰州城市学院电子与信息工程学院,兰州730070 [2]西北民族大学电气工程学院,兰州730030

出　　处：《吉林大学学报（理学版）》2018年第2期382-388,共7页Journal of Jilin University:Science Edition

基　　金：甘肃省科技攻关项目(批准号:242102310128)

摘　　要：针对当前数字信号调制方式识别方法易受噪声影响、识别误差较大等问题,设计一种基于小波神经网络的数字信号调制方式识别方法.首先采集数字信号,并从信号中提取调制识别特征,作为数字信号调制方式分类依据;然后采用小波神经网络建立数字信号调制方式识别的分类器,并选择粒子群优化算法确定神经网络的参数,实现数字信号调制方式识别;最后在MATLAB 2016平台上实现数字信号调制方式识别的仿真测试.测试结果表明,即使数字信号的信噪比较低时,小波神经网络仍可获得较理想的数字信号调制方式识别结果,且数字信号调制方式识别率高于对比方法,从而提高了数字信号调制方式识别性能.In view of the problem that the recognition method of digital signal modulation mode was easy to be affected by noise and the recognition error was large,we designed a recognition method of digital signal modulation mode based on wavelet neural network.Firstly,we collected digital signal and extracted the modulation recognition feature from the signal as the classification basis of the digital signal modulation mode.Secondly,we established classifier of digital signals modulation recognition based on neural network,and selected particle swarm optimization algorithm to determine the parameters of the neural network,so as to realize the digital signal modulation recognition.Finally,the simulation test of digital signals modulation recognition was realized on MATLAB 2016 platform.The test results show that,even if the signal-to-noise ratio of digital signal is low,the wavelet neural network can still obtain the ideal digital signal modulation recognition results,and the digital signal modulation recognition rate is higher than that of the contrast method,thus improving the performance of digital signal modulation recognition.

关 键 词：数字信号 调制方式 识别方法 神经网络 粒子群优化算法 分类器设计 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]