北京科技大学学报2012，Vol.34Issue(1)：6-11,6.
面向匹配决策问题的漏整合神经元稀疏ESN网络
Sparse ESN with a leaky integrator for matching decision-making problems
摘要
Abstract
A new sparse echo state network （ESN） with a leaky integrator, which is expected to has more neurophysiology characteristics, was proposed and trained using the online supervised learning method so as to make the modeling and prediction of the matching decision-making problem. To evaluate the matching decision-making performance of the network, three kinds of test datasets were set up and an estimation method based on the maximum correlation coefficient for the actual output and the desired one was present. Simulation experimental resuhs show that the proposed model can achieve a better decision-making performance with a less training time. Meanwhile the model has a better robustness on spiking interval change, shifting, and network noise.关键词
回声状态网络（ESN）/递归神经网络/决策/匹配/神经元Key words
echo state network （ESN）/recurrent neural networks/decision making/matching/neurons分类
信息技术与安全科学引用本文复制引用
杨博,程振波,邓志东..面向匹配决策问题的漏整合神经元稀疏ESN网络[J].北京科技大学学报,2012,34(1):6-11,6.基金项目
国家自然科学基金资助项目（90820305 （）
60775040 （）
60621062 （）
61005085） （）
中国科学院自动化研究所模式识别国家重点实验室开放合作基金项目 （）
