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A new type of Echo State Network based on nonlinear readout nodes
作者:WU Ri-na YANG Ling WANG Fang
来源:本站原创
更新时间:2014-3-13 10:40:00
正文:


1. School of Information Science and Engineering, Lanzhou University, Lanzhou,730000,China

                 2. Inner Mongolia Regional Training Base of CAPF, Hohhot, 010070, China

                          Contacts: Wu Ri-na, e-mail: wurina820109@sohu.com

 

Abstract: The classical Echo state network (ESN) cannot fully exploit its advantages in some work which characterize strong nonlinearity and high-order statistics. In order to overcome the shortcomings, this paper using the nonlinear readout nodes instead of the traditional linear readout nodes in classical ESN, Radical Basis Function (RBF) neural network was introduced to read out the reservoir state. Benchmark experiments on Lorenz chaotic time series and NARMA model identification shown that the proposed new type of ESN can improve the nonlinear characteristics and it’s performance exceeded the classical ESN in dealing with some higher degree of nonlinear system and model.

Keywords: Echo state network; linear regression; nonlinear readout; RBF;

 

 


 
REFERENCES

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[12] Levy Boccato, Diogo C. Soriano, Romis Attux and Fernando Jos´e Von Zuben. Performance Analysis of Nonlinear Echo State Network Readouts in Signal Processing Tasks. WCCI 2012 IEEE World Congress on Computational Intelligence June, 10-15, 2012 - Brisbane, Australia.

[13] ZHANG Dong-qing, NING Xuan-xi, LIU Xue-ni. On-line prediction of nonlinear time series using RBF neural networks. Control Theory & Applications, Vol. 26 No. 2 Feb. 2009:151-155.

[14] S. H. Strogatz, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry and Engineering. Westview Press, 2000.

[15] PANG Shi-wei, YU Kai-ping, ZOU Jing-xiang. “Identifying nonlinear time-varying structural system based on NARMA model”. JOURNAL OF HARBIN INSTITUTE OF TECHNOLOGY, Vol.40 No 1,Jan. 2008:12-16.

 

作者简介:

乌日娜,(1982-),硕士研究生,主要研究方向:通信系统智能信号处理。

 
 
   
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