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1994 | 86 | 3 | 427-433
Article title

Memory Properties of Non-Fully Interconnected Neural Network

Content
Title variants
Languages of publication
EN
Abstracts
EN
A model of a neural network consisting of two states neurons with the number N of (symmetric) synaptic connections per neuron treated as a variable was investigated numerically. Hebb's rule was used for storing uncorrelated patterns in the network. A maximal number of such patterns, which can be effectively retrieved by the network and the process of deterioration of the memory, is examined as a function of the number of synaptic connections per neuron. The influence of the number of neurons in the network as well as boundary conditions for the storage capacity of the network are discussed.
Keywords
EN
Publisher

Year
Volume
86
Issue
3
Pages
427-433
Physical description
Dates
published
1994-05
received
1994-02-04
(unknown)
1994-05-13
Contributors
  • Dept. of Applied Physics and Mathematics, Institute of Physics, Warsaw University of Technology, Koszykowa 75, 00-662 Warszawa, Poland
author
  • Dept. of Applied Physics and Mathematics, Institute of Physics, Warsaw University of Technology, Koszykowa 75, 00-662 Warszawa, Poland
References
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv86z316kz
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