https://doi.org/10.1140/epjb/s10051-026-01152-z
Research - Statistical and Nonlinear Physics
A physical approach to local energy injection control of neural networks
1
Department of Physics, Lanzhou University of Technology, 730050, Lanzhou, China
2
School of Microelectronics Industry-Education Integration, Lanzhou University of Technology, 730050, Lanzhou, China
3
School of Automation and Electrical Engineering, Lanzhou University of Technology, 730050, Lanzhou, China
a
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Received:
23
February
2026
Accepted:
9
March
2026
Published online:
23
March
2026
Abstract
In the neural network, 5 × 5 neurons in the local area are excited by energy injection, which an additive sub-branch circuit injects energy flow into the inductive ion channel, the branch circuit composed of an inductor of the neural circuit by using memristive stimuli within a finite frequency band. A control branch circuit (sub-branch circuit) is built to shunt energy flow from the neural circuit. The memristive current is filtered by the capacitor in the sub-branch circuit, then it is injected into one branch circuit of the neural circuit for continuous energy injection, which creates an energy source in the neural network, and a target wave is induced to occupy the network. It is different from the previous schemes that local periodical forcing is imposed on the membrane potential of each neuron directly, and our scheme emphasizes energy injection into the ion channels for further regulating the membrane potentials indirectly. The control mechanism is that local energy injection into ion channels will increase the energy level of finite neurons, and energy flow is diffused to excite more adjacent neurons accompanying the emergence of a target wave. The pacemaker depends on shunting current from ion channels of local finite neuron, and local energy injection into the ion channels excites finite neurons for further inducing ordered waves. It is also different from the scheme by blocking ion channels of neurons in the local area of the neural network, and our control strategy provides a physical approach and the function of ion channels is understood.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2026
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
