DocumentCode :
1509940
Title :
Complex-valued multistate neural associative memory
Author :
Jankowski, Stanislaw ; Lozowski, Andrzej ; Zurada, Jacek M.
Author_Institution :
Inst. of Electron. Fundamentals, Warsaw Univ. of Technol., Poland
Volume :
7
Issue :
6
fYear :
1996
fDate :
11/1/1996 12:00:00 AM
Firstpage :
1491
Lastpage :
1496
Abstract :
A model of a multivalued associative memory is presented. This memory has the form of a fully connected attractor neural network composed of multistate complex-valued neurons. Such a network is able to perform the task of storing and recalling gray-scale images. It is also shown that the complex-valued fully connected neural network may be considered as a generalization of a Hopfield network containing real-valued neurons. A computational energy function is introduced and evaluated in order to prove network stability for asynchronous dynamics. Storage capacity as related to the number of accessible neuron states is also estimated
Keywords :
Hopfield neural nets; content-addressable storage; Hopfield network; asynchronous dynamics; complex-valued multistate neural associative memory; computational energy function; fully connected attractor neural network; gray-scale image recall; gray-scale image storage; multivalued associative memory; network stability; storage capacity; Associative memory; Computer networks; Gray-scale; Hopfield neural networks; Image coding; Image recognition; Neural networks; Neurons; Stability; State estimation;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.548176
Filename :
548176
Link To Document :
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