DocumentCode :
2622943
Title :
A dynamical network capable of storing sequences of static or periodic patterns
Author :
Poteryaiko, Igor Yu
Author_Institution :
Dept. of Low Temp. Phys., Moscow State Univ., USSR
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
373
Abstract :
The author proposes a modification of the neural network model of B. Baird (1988,1989) in which the constraint of symmetrical interaction between the modes representing the patterns stored is eliminated. This makes it possible to construct the system with the ordered transitions between the patterns which were the stable attractors in the original model. Although in this case there is no strict evidence that the system does not have the chaotic behavior, a qualitative investigation and extensive numerical simulations show that the dynamics of the system can be described quite simply in terms of effective excitation wandering through the closed loop. Such motion implies the consequent activation of the static or periodic patterns stored in the network. Thus, it is shown that the model can exhibit more complex, but still programmable, behavior than was originally assumed by B. Baird
Keywords :
learning systems; neural nets; attractors; closed loop; dynamic neural nets; periodic pattern sequence storage; static pattern sequences; symmetrical interaction; Chaos; Equations; Limit-cycles; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170430
Filename :
170430
Link To Document :
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