CLC number:
On-line Access: 2024-05-28
Received: 2023-12-25
Revision Accepted: 2024-02-10
Crosschecked: 2024-05-28
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Citations: Bibtex RefMan EndNote GB/T7714
https://orcid.org/0000-0002-6127-000X
Feifei YANG, Lujie REN, Jun MA, Zhigang ZHU. Two simple memristive maps with adaptive energy regulation and digital signal process verification[J]. Journal of Zhejiang University Science A, 2024, 25(5): 382-394.
@article{title="Two simple memristive maps with adaptive energy regulation and digital signal process verification",
author="Feifei YANG, Lujie REN, Jun MA, Zhigang ZHU",
journal="Journal of Zhejiang University Science A",
volume="25",
number="5",
pages="382-394",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2300651"
}
%0 Journal Article
%T Two simple memristive maps with adaptive energy regulation and digital signal process verification
%A Feifei YANG
%A Lujie REN
%A Jun MA
%A Zhigang ZHU
%J Journal of Zhejiang University SCIENCE A
%V 25
%N 5
%P 382-394
%@ 1673-565X
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2300651
TY - JOUR
T1 - Two simple memristive maps with adaptive energy regulation and digital signal process verification
A1 - Feifei YANG
A1 - Lujie REN
A1 - Jun MA
A1 - Zhigang ZHU
J0 - Journal of Zhejiang University Science A
VL - 25
IS - 5
SP - 382
EP - 394
%@ 1673-565X
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2300651
Abstract: Mathematical models can produce desired dynamics and statistical properties with the insertion of suitable nonlinear terms, while energy characteristics are crucial for practical application because any hardware realizations of nonlinear systems are relative to energy flow. The involvement of memristive terms relative to memristors enables multistability and initial-dependent property in memristive systems. In this study, two kinds of memristors are used to couple a capacitor or an inductor, along with a nonlinear resistor, to build different neural circuits. The corresponding circuit equations are derived to develop two different types of memristive oscillators, which are further converted into two kinds of memristive maps after linear transformation. The hamilton energy function for memristive oscillators is obtained by applying the Helmholz theorem or by mapping from the field energy of the memristive circuits. The hamilton energy functions for both memristive maps are obtained by replacing the gains and discrete variables for the memristive oscillator with the corresponding parameters and variables. The two memristive maps have rich dynamic behaviors including coherence resonance under noisy excitation, and an adaptive growth law for parameters is presented to express the self-adaptive property of the memristive maps. A digital signal process (DSP) platform is used to verify these results. Our scheme will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map-energy calculation.
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