Published January 30, 2019 | Version v1
Journal article

Effects of initial conditions on the synchronization of the coupled memristor neural circuits

  • 1. Southwest University, Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering (China)

Description

The fourth basic two-terminal circuit element has been called the memristor because its resistance (conductance) depends on the complete past history of the memristor current (voltage), i.e., the initial charge (flux) condition at a given instant. This paper aims to provide some insight into the effects of the initial flux condition of the memristor synapse in the synchronization of two coupled memristor-based neural circuits. First, we build the coupled memristor-based FitzHugh–Nagumo circuits with the memristor synapse, and obtain the initial conditions by means of the flux-charge analysis method in the differential equations. Then, as a result of varying the initial conditions of the coupling memristor in the neural network, the details of synchronization with the parallel shift are derived theoretically by solving the nonhomogeneous error equations. These results of theoretical analyses have been confirmed by numerical simulations. Finally, we focus on the influence of the initial condition of the memristor on chaos generation for individual FitzHugh–Nagumo neuron and how to change chaotic state into stable periodic oscillation for a FitzHugh–Nagumo neuron in the synchronous neural network.

Additional details

Identifiers

Publishing Information

Journal Title
Nonlinear Dynamics
Journal Volume
95
Journal Issue
2
Journal Page Range
p. 1269-1282
ISSN
0924-090X

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
51097067
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
CHAOS THEORY; COMPUTERIZED SIMULATION; COUPLING; DIFFERENTIAL EQUATIONS; ELECTRIC POTENTIAL; ERRORS; NERVE CELLS; NEURAL NETWORKS; OSCILLATIONS; PERIODICITY; SYNCHRONIZATION; TRANSISTORS
Descriptors DEC
ANIMAL CELLS; EQUATIONS; MATHEMATICS; SEMICONDUCTOR DEVICES; SIMULATION; SOMATIC CELLS; VARIATIONS

Optional Information

Copyright
Copyright (c) 2019 Springer Nature B.V.