Reservoir Computing Trends

被引：269

作者：

Lukoševičius, Mantas ^{[1
]}

Jaeger, Herbert ^{[1
]}

Schrauwen, Benjamin ^{[2
]}

机构：

[1] Jacobs University Bremen, Campus Ring 1, Bremen

[2] Ghent University, Sint Pietersnieuwstraat 41, Ghent

来源：

KI - Kunstliche Intelligenz | 2012年 / 26卷 / 04期

关键词：

Echo state network; Recurrent neural network; Reservoir computing;

D O I：

10.1007/s13218-012-0204-5

中图分类号：

学科分类号：

摘要：

Reservoir Computing (RC) is a paradigm of understanding and training Recurrent Neural Networks (RNNs) based on treating the recurrent part (the reservoir) differently than the readouts from it. It started ten years ago and is currently a prolific research area, giving important insights into RNNs, practical machine learning tools, as well as enabling computation with non-conventional hardware. Here we give a brief introduction into basic concepts, methods, insights, current developments, and highlight some applications of RC. © 2012, Springer-Verlag.

引用

页码：365 / 371

页数：6

共 53 条

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