桂林电子科技大学学报2012，Vol.32Issue(2)：122-124,3.
基于小波神经网络的调制信号识别方法
A recognition method on modulation signal based on wavelet network
摘要
Abstract
In order to overcome single neural network some weakness that it is difficult to expand, modify and maintain the neural network with large categories, a recognition method based on wavelet and RBF network array is used to divide wireless communication modulation signals. The feature extractions of three kinds of analog signals and six digital signals are picked up by a wavelet decomposition method and then feature extractions are classified by RBF neural network array. The simulation results show that the design combined with the wavelet analysis and neural network array makes the modulation category detection system of the wireless communication signal to achieve a-bout 90% performance when SNR is ?0 dB, and the detection rate in the multiple categories is improved.关键词
小波分析/调制信号识别/特征提取/RBF/阵列网络Key words
wavelet analysis/ category detection/ feature extraction! RBF/ neural network array分类
信息技术与安全科学引用本文复制引用
姜茜,朱国魂,覃举存..基于小波神经网络的调制信号识别方法[J].桂林电子科技大学学报,2012,32(2):122-124,3.基金项目
广西科学研究与技术开发计划项目(1114006-3C) （1114006-3C）
