摘要
基于神经网络运算速度快,并行处理能力强的特点,本文以最小均方误差为准则,利用Hopfield神经网络特有的并行干扰抵消结构及其固有的能量函数快速下降特性,提出了基于Hopfield神经网络的并行干扰抵消多用户检测算法,既解决了局部最优的问题,又降低了MMSE的计算复杂度。
Based on the high speed and powerful parallel processing function of neural networks and MMSE criteria,using Hopfield neural network＇s PIC structure and its inherent rapid decline character in its Energy function,this paper present a Hopfield-based parallel inference-counteracting multi-user detection algorithm GMHNN,and proved this algorithm can converge to global minimum.
出处
《软件》
2012年第10期36-37,共2页
Software
关键词
HNN
GMHNN
移动终端
Hopfield neural network
GMHNN
mobile terminal
