Application of Improved Memristor in Character Associative Memory

WANG Leimin; CHENG Jiajun; HU Cheng; ZHOU Yingjiang; GE Mingfeng

doi:10.11999/JEIT220709

Volume 45 Issue 7

Jul. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(7): 2667-2674

WANG Leimin, CHENG Jiajun, HU Cheng, ZHOU Yingjiang, GE Mingfeng. Application of Improved Memristor in Character Associative Memory[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2667-2674. doi: 10.11999/JEIT220709

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WANG Leimin, CHENG Jiajun, HU Cheng, ZHOU Yingjiang, GE Mingfeng. Application of Improved Memristor in Character Associative Memory[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2667-2674. doi: 10.11999/JEIT220709

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Application of Improved Memristor in Character Associative Memory

doi: 10.11999/JEIT220709

WANG Leimin^{1, 2, 3
,
,},
CHENG Jiajun^{1, 2, 3},
HU Cheng⁴,
ZHOU Yingjiang⁵,
GE Mingfeng⁶

1.
School of Automation, China University of Geosciences, Wuhan 430074, China
2.
Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China
3.
Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China
4.
School of Mathematics and Systems Science, Xinjiang University, Urumqi 830017, China
5.
School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
6.
School of Mechanical and Electronic Information, China University of Geosciences, Wuhan 430074, China

Funds: The National Natural Science Foundation of China (62076229, 61963033, 62073301)

Received Date: 2022-05-31
Rev Recd Date: 2022-09-15

Available Online: 2022-11-20

Publish Date: 2023-07-10

Abstract

Abstract

Memristor is a very suitable electronic component for synapse of neural network because of its adjustable resistance, memory property and nano size. In order to build a memristor model more consistent with the characteristics of real physical memristors, an improved memristor model is proposed based on existing ones to overcome the problems of boundary locking, positive and negative voltage rate adjustment and the universality of circuit structure. Then combining Pavlov associative memory experiment and Hopfield neural network theory, the character associative memory circuit is designed in this paper. The circuit structure includes mainly input signal module, synaptic array module, activation function module and feedback control module. This circuit can solve the flexibility problem of using resistors as synaptic modules in traditional array modules, and can also realize the self-association function of third-order character blurred images. In addition, the circuit is similar to the convolutional computation module related to deep learning, and provides a theoretical basis for realizing memristor-based intelligent hardware.
- Memristor,
- Neural network,
- Circuit design,
- Associative memory

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References(28)

References

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