Analysis of Recurrent Analog Neural Networks
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Date
1998-06
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
In this paper, an original rigorous analysis of recurrent analog neural networks, which are built from opamp neurons, is presented. The analysis, which comes from the approximate model of the operational amplifier, reveals causes of possible non-stable states and enables to determine convergence properties of the network. Results of the analysis are discussed in order to enable development of original robust and fast analog networks. In the analysis, the special attention is turned to the examination of the influence of real circuit elements and of the statistical parameters of processed signals to the parameters of the network.
Description
Citation
Radioengineering. 1998, vol. 7, č. 2, s. 9-14. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/1998/98_02_02.pdf
http://www.radioeng.cz/fulltexts/1998/98_02_02.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en