An accelerating learning algorithm for block-diagonal recurrent neural networks

被引：0
|
作者：
Mastorocostas, Paris [1 ]
Varsamis, Dirnitris [1 ]
Mastorocostas, Constantinos [1 ]
Rekanos, Ioannis [1 ]
机构：
[1] Technol Educ Inst Serres, Dept Informat, Serres 62124, Greece
来源：
INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION JOINTLY WITH INTERNATIONAL CONFERENCE ON INTELLIGENT AGENTS, WEB TECHNOLOGIES & INTERNET COMMERCE, VOL 2, PROCEEDINGS | 2006年
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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：
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to be applied to dynamic systems. A comparative analysis with a series of algorithms and recurrent models is given, indicating the effectiveness of the proposed learning approach.
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页码：403 / +
页数：2
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