Coupled HR–HNN Neuron with a Locally Active Memristor

Author:

Huang Lili1ORCID,Wang Shaotian1ORCID,Lei Tengfei1ORCID,Huang Keyu2ORCID,Li Chunbiao3ORCID

Affiliation:

1. Collaborative Innovation Center of Memristive, Computing Application (CICMCA), Qilu Institute of Technology, Jinan 250200, P. R. China

2. School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China

3. School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China

Abstract

Local activity could be the source for complexity. In this study, a multistable locally active memristor is proposed, whose nonvolatile memory, as well as locally active characteristics, is validated by the power-off plot and DC [Formula: see text]–[Formula: see text] plot. Based on the two-dimensional Hindmarsh–Rose neuron and a one-dimensional Hopfield neuron, a simple neural network is constructed by connecting the two neurons with the locally active memristor. Coexisting multiple firing patterns under different initial conditions are investigated according to the controlled coupling factor. The results suggest that the system exhibits coexisting periodic and chaotic bursting with different firing patterns. Complex firing only occurs in the locally active area of the defined memristor, meanwhile the system shows a periodic oscillation in the passive area. Beyond this, the coupled neurons exhibit the specific phenomenon of attractor growing in the locally active region of the memristor. The circuit simulations by Power Simulation (PSIM) are included confirming the numerical simulations and theoretic analysis.

Funder

Natural Science Foundation of Shandong Province

Priority Academic Program Development of QILU Institute of Technology

Publisher

World Scientific Pub Co Pte Ltd

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