Optimal Hopfield Neural Network and Application for Multi-User Detection

摘要：

Hopfield neural network without learning rules, not need training, and not self-learning, to adjust weight by the design process of Lyapunov function, generalized penalty function is combined with the energy function of Hopfield neural network,, a more suitable structure of the new objective function is built based on the minimal average output energy norm, An improved Hopfield neural network method of achieving DS/CDMA blind multi-user detection is discussed. Simulation results show that that the algorithm significantly improved in bit error rate and anti-near-far effect.

关键词： Near-Far Effect Energy function Object function Bit error rate Penalty function

作者: WANG Hongbin ZHANG Li-yi

作者单位: Department of Computer Science Xinzhou Teachers University Xinzhou, China College of Information Engineering TianJin University of Commerce TianJin, China

会议类型: 国际会议

会议名称: The International Conference on Communication Software and Networks(2009 IEEE通信软件与网络国际会议 ICCSN 2009)

会议地点: 成都

会议语种:英文

页码: 567-570

在线出版日期: 2009-02-20（万方平台首次上网日期，不代表论文的发表时间）