Automatic Identification System for Railway Wireless Communication Interfer-ence Signals Based on Deep Learning Algorithms
A railway wireless communication interference signal automatic recognition system based on deep learning algorithm is proposed to address the problems of chaotic signal interference,low accuracy of automatic recognition,and difficulty in type discrimination in the process of railway wireless communication.The automatic identification system for wireless communication interference signals mainly targets the interference signal problems faced by railway wireless communication processes,such as noise amplitude modulation,radio frequency noise,and noise frequency modulation.The system optimizes the BP neural network by improving the beetle antennae algorithm,using domain moment skewness and domain moment kurtosis as feature parameters for automated recognition and judgment.After actual experimental verification,the interference signal automatic recognition system designed in this article is faster and more accurate,and the automation recognition accuracy is higher.
beetle antennae algorithmBP neural networkdomain moment skewnessdomain moment kurtosisrailway communication interference
NETL
NSTL
万方数据
维普
