Research on the Blind Equalization technology Based on the Complex BP Neural Network with Tunable Activation Functions

摘要：

　　The blind equalization technology was proposed to reduce the inter-symbol interference(ISI)without training signal sequences.It saved the bandwidth resources and increased the correctness of signal transmissions.The blind equalizers had consequently been an indispensable part of the communication system.The blind equalization technology based on backward propagation(BP)neural networks had been widely studied with a variety of developments and improvements.In this paper,a new equalizer based on the complex BP neural networks with tunable activation functions(TAF)is proposed,algorithms were derived and simulations were done.Results showed that the proposed equalizer would work faster with less square errors than that based on traditional BP neural networks.It worked very well with zero byte-error rates(BER)when signal-to-noise(SNR)of the communication system was larger than 15 dB.

关键词： blind equalization technology complex signal backward propagation neural network tunable activation function

作者: Juan ZHAO Zheng-Ming GAO

作者单位: School of Electronics and Information Engineering,Jingchu University of Technology,Jingmen China Baoji Research Institute of High Technology,Baoji,China

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 813-817

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）