Improved Learning Experience Memristor Model and Application as Neural Network Synapse
This paper proposes a memristor model, named learning experience memristor (LEM), for using as synapse in the associative neural network. The properties of LEM are discussed under different external voltages. And then, we design a new feedback learning rule, all input feedback (AIF). An associative...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8625409/ |
| _version_ | 1818415922065440768 |
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| author | Xiaohong Zhang Keliu Long |
| author_facet | Xiaohong Zhang Keliu Long |
| author_sort | Xiaohong Zhang |
| collection | DOAJ |
| description | This paper proposes a memristor model, named learning experience memristor (LEM), for using as synapse in the associative neural network. The properties of LEM are discussed under different external voltages. And then, we design a new feedback learning rule, all input feedback (AIF). An associative neural network-based the AIF law and LEM synapse is constructed and analyzed, and the associative neural network incorporates learning experience behavior, forgetting, and threshold functions. The properties of LEM are also verified through PSpice simulation. The associative neural network circuit based on AIF law and LEM are constructed and simulated using PSpice, the simulation results are analyzed sufficiently. Finally, different memristors are used as synapses in the associative neural network, and we analyze and compare the simulation results. All simulation results show that the associative neural network incorporating LEM synapses and AIF learning law exhibits good performance, mimicking biological neural networks, and self-learning behavior. |
| first_indexed | 2024-12-14T11:42:41Z |
| format | Article |
| id | doaj.art-2bb8ff61d9444da2ba10e7d9170b1e94 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T11:42:41Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2bb8ff61d9444da2ba10e7d9170b1e942022-12-21T23:02:45ZengIEEEIEEE Access2169-35362019-01-017152621527110.1109/ACCESS.2019.28946348625409Improved Learning Experience Memristor Model and Application as Neural Network SynapseXiaohong Zhang0https://orcid.org/0000-0003-2481-2663Keliu Long1School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, ChinaSchool of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, ChinaThis paper proposes a memristor model, named learning experience memristor (LEM), for using as synapse in the associative neural network. The properties of LEM are discussed under different external voltages. And then, we design a new feedback learning rule, all input feedback (AIF). An associative neural network-based the AIF law and LEM synapse is constructed and analyzed, and the associative neural network incorporates learning experience behavior, forgetting, and threshold functions. The properties of LEM are also verified through PSpice simulation. The associative neural network circuit based on AIF law and LEM are constructed and simulated using PSpice, the simulation results are analyzed sufficiently. Finally, different memristors are used as synapses in the associative neural network, and we analyze and compare the simulation results. All simulation results show that the associative neural network incorporating LEM synapses and AIF learning law exhibits good performance, mimicking biological neural networks, and self-learning behavior.https://ieeexplore.ieee.org/document/8625409/Associative memorylearning experience behaviormemristor synapse |
| spellingShingle | Xiaohong Zhang Keliu Long Improved Learning Experience Memristor Model and Application as Neural Network Synapse IEEE Access Associative memory learning experience behavior memristor synapse |
| title | Improved Learning Experience Memristor Model and Application as Neural Network Synapse |
| title_full | Improved Learning Experience Memristor Model and Application as Neural Network Synapse |
| title_fullStr | Improved Learning Experience Memristor Model and Application as Neural Network Synapse |
| title_full_unstemmed | Improved Learning Experience Memristor Model and Application as Neural Network Synapse |
| title_short | Improved Learning Experience Memristor Model and Application as Neural Network Synapse |
| title_sort | improved learning experience memristor model and application as neural network synapse |
| topic | Associative memory learning experience behavior memristor synapse |
| url | https://ieeexplore.ieee.org/document/8625409/ |
| work_keys_str_mv | AT xiaohongzhang improvedlearningexperiencememristormodelandapplicationasneuralnetworksynapse AT keliulong improvedlearningexperiencememristormodelandapplicationasneuralnetworksynapse |