Analysis of Recurrent Analog Neural Networks
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 pro...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Spolecnost pro radioelektronicke inzenyrstvi
1998-06-01
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| Series: | Radioengineering |
| Online Access: | http://www.radioeng.cz/fulltexts/1998/98_02_02.pdf |
| _version_ | 1819095026903285760 |
|---|---|
| author | Z. Raida Z. Tobes |
| author_facet | Z. Raida Z. Tobes |
| author_sort | Z. Raida |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-21T23:36:46Z |
| format | Article |
| id | doaj.art-ef10e259550e4b419f87f5ea7f9072f6 |
| institution | Directory Open Access Journal |
| issn | 1210-2512 |
| language | English |
| last_indexed | 2024-12-21T23:36:46Z |
| publishDate | 1998-06-01 |
| publisher | Spolecnost pro radioelektronicke inzenyrstvi |
| record_format | Article |
| series | Radioengineering |
| spelling | doaj.art-ef10e259550e4b419f87f5ea7f9072f62022-12-21T18:46:21ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25121998-06-0172Analysis of Recurrent Analog Neural NetworksZ. RaidaZ. TobesIn 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.www.radioeng.cz/fulltexts/1998/98_02_02.pdf |
| spellingShingle | Z. Raida Z. Tobes Analysis of Recurrent Analog Neural Networks Radioengineering |
| title | Analysis of Recurrent Analog Neural Networks |
| title_full | Analysis of Recurrent Analog Neural Networks |
| title_fullStr | Analysis of Recurrent Analog Neural Networks |
| title_full_unstemmed | Analysis of Recurrent Analog Neural Networks |
| title_short | Analysis of Recurrent Analog Neural Networks |
| title_sort | analysis of recurrent analog neural networks |
| url | http://www.radioeng.cz/fulltexts/1998/98_02_02.pdf |
| work_keys_str_mv | AT zraida analysisofrecurrentanalogneuralnetworks AT ztobes analysisofrecurrentanalogneuralnetworks |