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CLC number: TP183; TN6

On-line Access: 2021-07-12

Received: 2020-02-23

Revision Accepted: 2020-08-23

Crosschecked: 2021-05-08

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Yi-fei Pu


Qiuyan He


Xiao Yuan


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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.6 P.862-876


Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit

Author(s):  Yifei Pu, Bo Yu, Qiuyan He, Xiao Yuan

Affiliation(s):  College of Computer Science, Sichuan University, Chengdu 610065, China; more

Corresponding email(s):   heqiuyan789@163.com, yuanxiao@scu.edu.cn

Key Words:  Fractional calculus, Fracmemristor, Fracmemristance, Fractional-order memristor, Fractional-order memristive synapses

Yifei Pu, Bo Yu, Qiuyan He, Xiao Yuan. Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(6): 862-876.

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author="Yifei Pu, Bo Yu, Qiuyan He, Xiao Yuan",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit
%A Yifei Pu
%A Bo Yu
%A Qiuyan He
%A Xiao Yuan
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 6
%P 862-876
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000085

T1 - Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit
A1 - Yifei Pu
A1 - Bo Yu
A1 - Qiuyan He
A1 - Xiao Yuan
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 6
SP - 862
EP - 876
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000085

We propose a novel circuit for the fractional-order memristive neural synaptic weighting (FMNSW). The introduced circuit is different from the majority of the previous integer-order approaches and offers important advantages. Since the concept of memristor has been generalized from the classic integer-order memristor to the fractional-order memristor (fracmemristor), a challenging theoretical problem would be whether the fracmemristor can be employed to implement the fractional-order memristive synapses or not. In this research, characteristics of the FMNSW, realized by a pulse-based fracmemristor bridge circuit, are investigated. First, the circuit configuration of the FMNSW is explained using a pulse-based fracmemristor bridge circuit. Second, the mathematical proof of the fractional-order learning capability of the FMNSW is analyzed. Finally, experimental work and analyses of the electrical characteristics of the FMNSW are presented. Strong ability of the FMNSW in explaining the cellular mechanisms that underlie learning and memory, which is superior to the traditional integer-order memristive neural synaptic weighting, is considered a major advantage for the proposed circuit.




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