智能系统学报2016，Vol.11Issue(6)：758-767,10.DOI:10.11992/tis.201612015
随机权神经网络研究现状与展望
Review and prospect on neural networks with random weights
摘要
Abstract
A randomized learning algorithm in a neural network, which can overcome the difficulty of slow convergence and local minimum inherently in the traditional gradient-based learning algorithms, has recently become a hot topic in the field of neural networks.Some neural networks with random weights using randomized learning algorithms have been proposed.The aim of this paper summarizes the current research on neural networks with random weights and provides some views about its development trends.First, a simplified model of a neural network with random weights was proposed, and the randomized learning algorithm was summarized, based on the simplified model.Then, a review on neural networks with random weights was given, and the performance of several different neural networks with random weights was analyzed, based on the simplified model.Finally, several views on neural networks with random weights are presented.关键词
随机权神经网络/前馈神经网络/递归神经网络/级联神经网络/随机学习算法Key words
neural network with random weights/feedforward neural network/recurrent neural network/cascade neural network/randomized learning algorithm分类
信息技术与安全科学引用本文复制引用
乔俊飞,李凡军,杨翠丽..随机权神经网络研究现状与展望[J].智能系统学报,2016,11(6):758-767,10.基金项目
国家自然科学基金项目(61533002,61603012) （61533002,61603012）
北京市自然科学基金项目(Z141100001414005) （Z141100001414005）
北京市教委基金项目(km201410005001,KZ201410005002). （km201410005001,KZ201410005002）
