论文题目 |
Adaptive lasso echo state network for time series prediction |
作者 |
赵静,Wang Lei(外),杨翠丽(外) |
年度 |
2017 |
发表/出版时间 |
2017/12/29 |
发表期刊/会议 |
Proceedings - 2017 Chinese Automation Congress, CAC 2017 |
关键词 |
echo state network, collinearity problem, |
摘要 |
Echo state network (ESN), a novel recurrent
neural network, has a randomly and sparsely connected
reservoir. Since the reservoir is very large, the collinearity
problem may exist in ESN. To overcome this problem and
get a sparse architecture, an adaptive lasso echo state
network (ALESN) is proposed, in which the adaptive lasso
algorithm is used to calculate the output weights. The
proposed ALESN can deal with the collinearity problem
and has the oracle property. Simulation results show that
the proposed ALESN has better performance and more
compact architecture than some other existing methods. |