DocumentCode
312575
Title
Parallel learning and regeneration of images using a structured recurrent neural network
Author
Date, Osamu ; Miyanaga, Yoshikazu ; Tochinai, Koji
Author_Institution
Dept. of Electron. & Inf. Eng., Hokkaido Univ., Sapporo, Japan
Volume
1
fYear
1997
fDate
9-12 Jun 1997
Firstpage
533
Abstract
A recurrent neural network (RNN) has been already studied for some applications and have been also demonstrated for time series. In this paper, a new structured RNN is introduced. This network is designed with some groups of neurons and it is suitable for parallel processing and for realizing chaotic data. In particular, this network is actually implemented in a parallel computer and the performance of this network is explored for image memorizing
Keywords
chaos; image processing; learning (artificial intelligence); parallel processing; recurrent neural nets; image regeneration; learning; parallel processing; structured recurrent neural network; Application software; Chaos; Computer networks; Concurrent computing; Multi-layer neural network; Neural networks; Neurons; Parallel processing; Recurrent neural networks; Regeneration engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on
Print_ISBN
0-7803-3583-X
Type
conf
DOI
10.1109/ISCAS.1997.608798
Filename
608798
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