Some properties of asymmetric Hopfield neural networks with finite time of transition between states
There were implemented samples of asymmetric Hopfield neural networks which have finite time of transition from one state to another. It was shown that in such systems, various oscillation modes could occur. It was revealed that the oscillation of the output signal of certain neuron could be treated...
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De Gruyter
2016-11-01
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| Series: | Open Engineering |
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| Online Access: | http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0047/eng-2016-0047.xml?format=INT |
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doaj-182ab2ca97da488189c5dd387835b9212020-11-24T21:12:53ZengDe GruyterOpen Engineering2391-54392016-11-016110.1515/eng-2016-0047eng-2016-0047Some properties of asymmetric Hopfield neural networks with finite time of transition between statesSuleimenov Ibragim0Mun Grigoriy1Panchenko Sergey2Pak Ivan3Almaty University of Power Engineering and Telecommunications, Almaty, KazakhstanAl-Farabi Kazakh National UniversityAlmaty University of Power Engineering and Telecommunications, Almaty, KazakhstanInstitute of Information and Computational Technologies, Almaty, KazakhstanThere were implemented samples of asymmetric Hopfield neural networks which have finite time of transition from one state to another. It was shown that in such systems, various oscillation modes could occur. It was revealed that the oscillation of the output signal of certain neuron could be treated as extra logical variable, which describes the state of the neuron. Asymmetric Hopfield neural networks are described in terms of ternary logic. Such logic may be employed in image recognition procedure.http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0047/eng-2016-0047.xml?format=INTartificial neural networks autooscillations flip flop image recognition bureaucracy management |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Suleimenov Ibragim Mun Grigoriy Panchenko Sergey Pak Ivan |
| spellingShingle |
Suleimenov Ibragim Mun Grigoriy Panchenko Sergey Pak Ivan Some properties of asymmetric Hopfield neural networks with finite time of transition between states Open Engineering artificial neural networks autooscillations flip flop image recognition bureaucracy management |
| author_facet |
Suleimenov Ibragim Mun Grigoriy Panchenko Sergey Pak Ivan |
| author_sort |
Suleimenov Ibragim |
| title |
Some properties of asymmetric Hopfield neural
networks with finite time of transition between
states |
| title_short |
Some properties of asymmetric Hopfield neural
networks with finite time of transition between
states |
| title_full |
Some properties of asymmetric Hopfield neural
networks with finite time of transition between
states |
| title_fullStr |
Some properties of asymmetric Hopfield neural
networks with finite time of transition between
states |
| title_full_unstemmed |
Some properties of asymmetric Hopfield neural
networks with finite time of transition between
states |
| title_sort |
some properties of asymmetric hopfield neural
networks with finite time of transition between
states |
| publisher |
De Gruyter |
| series |
Open Engineering |
| issn |
2391-5439 |
| publishDate |
2016-11-01 |
| description |
There were implemented samples of asymmetric
Hopfield neural networks which have finite time of transition
from one state to another. It was shown that in such
systems, various oscillation modes could occur. It was revealed
that the oscillation of the output signal of certain
neuron could be treated as extra logical variable, which
describes the state of the neuron. Asymmetric Hopfield
neural networks are described in terms of ternary logic.
Such logic may be employed in image recognition procedure. |
| topic |
artificial neural networks autooscillations flip flop image recognition bureaucracy management |
| url |
http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0047/eng-2016-0047.xml?format=INT |
| work_keys_str_mv |
AT suleimenovibragim somepropertiesofasymmetrichopfieldneuralnetworkswithfinitetimeoftransitionbetweenstates AT mungrigoriy somepropertiesofasymmetrichopfieldneuralnetworkswithfinitetimeoftransitionbetweenstates AT panchenkosergey somepropertiesofasymmetrichopfieldneuralnetworkswithfinitetimeoftransitionbetweenstates AT pakivan somepropertiesofasymmetrichopfieldneuralnetworkswithfinitetimeoftransitionbetweenstates |
| _version_ |
1716749599138381824 |