DocumentCode
1064668
Title
Locally recurrent globally feedforward networks: a critical review of architectures
Author
Tsoi, Ah Chung ; Back, Andrew D.
Author_Institution
Dept. of Electr. & Comput. Eng., Queensland Univ., St. Lucia, Qld., Australia
Volume
5
Issue
2
fYear
1994
fDate
3/1/1994 12:00:00 AM
Firstpage
229
Lastpage
239
Abstract
In this paper, we will consider a number of local-recurrent-global-feedforward (LRGF) networks that have been introduced by a number of research groups in the past few years. We first analyze the various architectures, with a view to highlighting their differences. Then we introduce a general LRGF network structure that includes most of the network architectures that have been proposed to date. Finally we will indicate some open issues concerning these types of networks
Keywords
feedforward neural nets; recurrent neural nets; locally recurrent globally feedforward neural networks; Artificial neural networks; Australia Council; Control systems; Delay; Finite impulse response filter; Input variables; Multilayer perceptrons; Neurofeedback; Neurons; Transfer functions;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.279187
Filename
279187
Link To Document