As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.

ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。

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In this paper, the traditional echo state network (ESN) through the structure and learning mechanism of the study, on the echo state network prediction method of chaotic time series.

本文主要通过对传统回声状态网络(esn)的结构和学习机理的研究，探讨了回声状态网络对混沌时间序列的预测方法。

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