NDLI: Bidirectional neural networks and class prototypes

Content Provider	IEEE Xplore Digital Library
Author	Nejad, A.F. Gedeon, T.D.
Copyright Year	1995
Description	Author affiliation: Dept. of Artificial Intelligence, New South Wales Univ., Sydney, NSW, Australia (Nejad, A.F.; Gedeon, T.D.)
Abstract	Among the numerous existing neural network models, there are only a few bidirectional neural networks. None of these bidirectional models are based on multilayer perceptrons. These models also have limitations which have prevented their popularity. The authors have designed bidirectional neural networks (BDNNs) based on multilayer perceptrons trained by a generalised form of the error backpropagation algorithm. They can be trained as either associative memories or cluster centroid finders. This gives the network new abilities and enables the authors to design powerful data representation techniques which are a key factor in reducing network generalisation error. The authors demonstrate applications of this approach to extracting meaning from neural networks, and finding the centers of clusters. This work could be a step towards simulating via the behaviour of artificial neural networks clustering methods closer to that of the biological brain. BDNNs may also be used as a simulation tool for evaluating some major cognitive psychology theories such as prototypes and dual-code theory. The successful and promising results of applying BDNNs on two real world problems (including missing and noisy attributes) as well as some artificial data sets is reported.
Starting Page	1322
Ending Page	1327
File Size	585756
Page Count	6
File Format	PDF
ISBN	0780327683
DOI	10.1109/ICNN.1995.487348
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-11-27
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Prototypes Multilayer perceptrons Artificial neural networks Biological system modeling Brain modeling Algorithm design and analysis Multi-layer neural network Backpropagation algorithms Associative memory
Content Type	Text
Resource Type	Article

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