摘要
提出一种基于改进神经网络的数字调制信号识别方法.首先建立调制信号模型,在正交调制载波上构建扩频通信系统,然后采用QPSK调制方式和变结构神经网络模型,对调制信号进行解调和识别.仿真实验结果表明,改进后的信号识别方法有效地改善了信号扩频特性和调制性能,提高了数字调制信号识别的抗干扰能力,数字调制信号识别率高,识别性能好.
Digital modulation recognition algorithm based on improved neural network is proposed. Firstly,modulated signal model is established and constructs spread spectrum communication system in the quadrate modulated carrier, and then QPSK modulation and variable structure neural network model： are used to signal demodulation and recognition. The simulation experimental results show that the proposed model can improve signal spread spectrum and modulation performance effectively, the anti-jamming ability of digital modulation signal recognition is improved, the recognition rate of digital modulation signal is high, and the recognition performance is good.
作者
刘翔
LIU Xiang(Urban Vocational College of Sichuan,Chengdu 610000,China)
出处
《内蒙古师范大学学报（自然科学汉文版）》
CAS
北大核心
2017年第2期200-203,207,共5页
Journal of Inner Mongolia Normal University(Natural Science Edition)
基金
四川省科技攻关项目(142102310125)
关键词
数字调制信号
神经网络
解调
识别
digital modulation signal
neural network： demodulation： r^et^tTnltimn
