摘要
回声状态网络是近年来新兴的一种递归神经网络,独特而简单的训练方式以及高精度的训练结果已使其成为当前研究的热点之一.在该网络中,引入了储备池计算模式这一新的神经网络的建设方案,克服了之前网络模型基于梯度下降的学习算法所难以避免的收敛慢和容易陷入局部极小等问题.围绕这种新型网络结构,国内外许多学者开展了多样的研究.本文全面深入介绍了回声状态网络这一新兴技术,讨论了回声状态网络的优缺点,并综合近年的研究现状,总结了回声状态网络的主要研究工作进展和未来的研究方向.
The echo state network（ESN） is a novel kind of recurrent neural network and has recently become a hot topic for its easy and distinctive training method along with high performance.In ESN,the reservoir computing method is introduced,which is a completely new approach used to design a recurrent neural network.By comparing this novel model with existing recurrent neural network models,it can overcome the difficulty encountered in slow convergence and local minimum in the gradient descent based training algorithm.Currently,there is considerable enthusiasm for the research and application of ESN.A review on ESN is presented in this paper.The advantages and drawbacks of ESN and various improvements are analyzed.Finally,some future research directions are also discussed.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2012年第2期217-222,共6页
Journal of University of Science and Technology Beijing
基金
国家自然科学基金资助项目(61174103
61074066
61004021)
中央高校基本科研业务费专项资金资助项目(FRF--TP--11--002B)
关键词
回声状态网络
储备池计算
递归神经网络
echo state networks
reservoir computing
recurrent neural networks
作者简介
通信作者:罗熊,E-mail:xluo@ustb.edu.cn
