Optimization of parameters of echo state network and its application to underwater robot

被引：0

作者：

Ishii, K ^{[1
]}

van der Zant, T ^{[1
]}

Becanovic, V ^{[1
]}

Plöger, P ^{[1
]}

机构：

[1] Kyushu Inst Technol, Kitakyushu, Fukuoka, Japan

来源：

SICE 2004 ANNUAL CONFERENCE, VOLS 1-3 | 2004年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Echo State Networks (ESNs) use a recurrent artificial neural network as a reservoir. Finding a good one depends on choosing the right parameters for the generation of the reservoir, intuition and luck. The method proposed in this article eliminates the need for the tuning by hand by replacing it with a double evolutionary computation. First a broad search to find the right parameters which generate the reservoir is used. Then a search directly on the connectivity matrices fine-tunes the ESN. Both steps show improvements over other known methods for an experimental limit-cycle dataset of the Twin-Burger underwater robot.

引用

页码：2800 / 2805

页数：6

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