Exponential Synchronization of Memristive HIndmarsh-Rose Neural Networks

2022/09/05 by Yuncheng You, You, Yuncheng · 2 citations
Computer Science · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Analysis of PDEs (math.AP) #FOS: Mathematics #Neural Networks Stability and Synchronization #stochastic dynamics and bifurcation

paper · pdf · doi:10.48550/arxiv.2209.01946

openalex publication_date 2022/09/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A new model of neural networks described by the memristive and diffusive Hindmarsh-Rose equations is proposed. Globally dissipative dynamics is shown with absorbing sets in the state spaces. Through sharp and uniform grouping estimates and by leverage of integral inequalities tackling the linear network coupling against the memristive nonlineariry, it is rigorously proved that exponential synchronization at a uniform convergence rate occurs when the coupling strengths satisfy the threshold conditions quantitatively expressed by the parameters.

Cited by

• Robust Synchronization of Time-Fractional Memristive Hopfield Neural Networks
• Approximate Synchronization of Memristive Hopfield Neural Networks

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