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Fractional-ordermemristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit
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Yi-fei PU, Bo YU, Qiu-yan HE, Xiao YUAN. Fractional-ordermemristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="Fractional-ordermemristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit",
author="Yi-fei PU, Bo YU, Qiu-yan HE, Xiao YUAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000085"
}
%0 Journal Article
%T Fractional-ordermemristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit
%A Yi-fei PU
%A Bo YU
%A Qiu-yan HE
%A Xiao YUAN
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000085
TY - JOUR
T1 - Fractional-ordermemristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit
A1 - Yi-fei PU
A1 - Bo YU
A1 - Qiu-yan HE
A1 - Xiao YUAN
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000085
Abstract: This study proposes a novel circuit for the fractional-order memristive neural synaptic weighting. The
introduced circuit is different from the majority of the previous integer-order approaches and offers important
advantages. Since the concept of memristor is 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
fractional-order memristive neural synaptic weighting (FMNSW), realized by pulse-based fracmemristor bridge
circuit, are investigated. First, the circuit configuration of the FMNSWis 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 underlies learning and memory, which is superior to the
traditional integer-order memristive neural synaptic weightings is considered a major advantage for the proposed
circuit.
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