Analysis of Recurrent Analog Neural Networks
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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.
Keywordsanalog recurrent networks, convergence properties, stability, modelling of operational amplifiers
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 1998, vol. 7, č. 2, s. 9-14. ISSN 1210-2512
- 1998/2