基于拉格朗日优化神经网络的盲多用户检测

Wang Hong-bin, Zhang Li-yi, Wang Hua-kui, Li Fu-ping
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引用次数: 1

摘要

本文概述了一种拉格朗日优化神经网络原理,它克服了传统神经网络存在惩罚函数思想的缺陷,直接处理不等式约束,减小网络规模和复杂度,提出了一种基于拉格朗日神经网络的新型优化神经网络,并通过计算机仿真表明,该算法在错误率性能方面有了改进,收敛速度也明显提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind multi-user detection based on lagrange optimization neural network
A kind of Lagrange principle of optimizing neural network is sketched in the paper, it has overcome the traditional defect based on that the neural network which punish function thought exists deal with inequality restraint directly reduce network size and complexity a kind of new optimization neural network Based on the Lagrange neural network, proposed a kind of blind multi-user detection algorithm, and indicated through the computer simulation, this algorithm has the improvement in the error rate performance aspect, the convergence rate also obviously enhances.
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