A new memristive map neuron, self-regulation and coherence resonance

Binchi Wang, Xiaofeng Zhang (), Zhigang Zhu and Guodong Ren
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Binchi Wang: Lanzhou University of Technology
Xiaofeng Zhang: Lanzhou University of Technology
Zhigang Zhu: Lanzhou University of Technology
Guodong Ren: Lanzhou University of Technology

The European Physical Journal B: Condensed Matter and Complex Systems, 2024, vol. 97, issue 8, 1-12

Abstract: Abstract Activation of firing patterns requires continuous energy exchange between magnetic and electric field in the neurons. Complexity of ion channels supports energy diversity among capacitive, inductive and memristive channel, and then the Calcium, sodium and potassium flows are pumped and diffused to trigger suitable firing modes in the neural activities. In this work, a magnetic flux-controlled memristor connected with an inductor in series is used to describe the physical effect of propagated ions, and an additive nonlinear resistor and a capacitor are connected to design a simple neural circuit. A memristive neuron model is suggested for dynamical analysis and energy description. Furthermore, linear transformation including time scale is used to convert this memristive oscillator into an equivalent memristive map. Energy function is given for this memristive map and an adaptive control law is used to control the mode transition in this map neuron. Furthermore, coherence resonance is discussed under noisy disturbance. Graphical abstract

Date: 2024
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DOI: 10.1140/epjb/s10051-024-00760-x

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