DocumentCode
1944246
Title
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
Author
Mastorocostas, Paris ; Varsamis, Dimitris ; Mastorocostas, Constantinos ; Rekanos, Ioannis
Author_Institution
Dept. of Informatics, Technol. Educational Inst. of Serres
Volume
2
fYear
2005
fDate
28-30 Nov. 2005
Firstpage
403
Lastpage
408
Abstract
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
Keywords
backpropagation; recurrent neural nets; accelerating learning algorithm; block-diagonal recurrent neural network; dynamic system; modified resilient backpropagation algorithm; static model; Acceleration; Algorithm design and analysis; Backpropagation algorithms; Control systems; Educational technology; Informatics; Neurofeedback; Neurons; Recurrent neural networks; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location
Vienna
Print_ISBN
0-7695-2504-0
Type
conf
DOI
10.1109/CIMCA.2005.1631502
Filename
1631502
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