https://doi.org/10.1140/epjs/s11734-025-01734-5
Regular Article
Exploring chaotic dynamics in cascaded ReLU-type HNN with current stimuli and memristive electromagnetic induction
1
School of Electrical and Information Engineering, Jiangsu University of Technology, 213001, Changzhou, China
2
School of Artificial Intelligence, Nanjing University of Information Science and Technology, 210044, Nanjing, China
3
Dodd Walls Centre for Photonics and Quantum Technologies, Department of Physics, The University of Auckland, 1010, Auckland, New Zealand
Received:
19
March
2025
Accepted:
3
June
2025
Published online:
13
June
2025
This paper investigates the chaotic dynamics of a cascaded ReLU-type Hopfield neural network (RHNN) with various external stimuli, including direct current (DC), alternating current (AC), and electromagnetic radiation. In particular, when a neuron is affected by external electromagnetic radiation, the membrane potential of the neuron will fluctuate, which in turn stimulates a time-varying electromagnetic field and feedbacks the dynamic process of modulating the membrane potential. The flux-controlled memristor inherently characterizes the coupling relationship between magnetic flux and charge. Therefore, it can be used as an effective modeling tool for simulating the electromagnetic induction mechanism of neuronal membrane potential. Numerical simulations reveal that DC stimulus can induce transient chaos in the RHNN, while AC stimulus leads to periodic and chaotic behaviors with complex bifurcations. Moreover, varying the intensity of electromagnetic radiation significantly modulates the dynamic patterns of the neural network, resulting in the occurrence of initial-associated coexisting bi-stable patterns. Finally, these complex phenomena are validated through the developed analog circuit, and the random sequences generated by the model are also verified by the standard tests for Pseudo-random number generators (PRNG). The explorations provide valuable insights into neuron modeling and are expected to facilitate potential applications in functional neuron design.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
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.
