| INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
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A phenomenological memristor model for synaptic memory and learning behaviors |
| Nan Shao(邵楠)1, Sheng-Bing Zhang(张盛兵)1, Shu-Yuan Shao(邵舒渊)2 |
1. School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China |
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Abstract Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials. These properties include the forgetting effect, the transition from short-term memory (STM) to long-term memory (LTM), learning-experience behavior, etc. The mathematical model of this kind of memristor would be very important for its theoretical analysis and application design. In our analysis of the existing memristor model with these properties, we find that some behaviors of the model are inconsistent with the reported experimental observations. A phenomenological memristor model is proposed for this kind of memristor. The model design is based on the forgetting effect and STM-to-LTM transition since these behaviors are two typical properties of these memristors. Further analyses of this model show that this model can also be used directly or modified to describe other experimentally observed behaviors. Simulations show that the proposed model can give a better description of the reported memory and learning behaviors of this kind of memristor than the existing model.
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Received: 18 March 2017
Revised: 04 July 2017
Accepted manuscript online:
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PACS:
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85.35.-p
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(Nanoelectronic devices)
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73.43.Cd
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(Theory and modeling)
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87.19.lv
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(Learning and memory)
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Corresponding Authors:
Nan Shao
E-mail: shao@mail.nwpu.edu.cn
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Cite this article:
Nan Shao(邵楠), Sheng-Bing Zhang(张盛兵), Shu-Yuan Shao(邵舒渊) A phenomenological memristor model for synaptic memory and learning behaviors 2017 Chin. Phys. B 26 118501
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