Dynamic behaviors of hyperbolic-type memristor-based Hopfield neural network considering synaptic crosstalk
Open Access
- 1 March 2020
- journal article
- conference paper
- Published by AIP Publishing in Chaos: An Interdisciplinary Journal of Nonlinear Science
- Vol. 30 (3) , 033108
Abstract
Crosstalk phenomena taking place between synapses can influence signal transmission and, in some cases, brain functions. It is thus important to discover the dynamic behaviors of the neural network infected by synaptic crosstalk. To achieve this, in this paper, a new circuit is structured to emulate the Coupled Hyperbolic Memristors, which is then utilized to simulate the synaptic crosstalk of a Hopfield Neural Network (HNN). Thereafter, the HNN’s multi-stability, asymmetry attractors, and anti-monotonicity are observed with various crosstalk strengths. The dynamic behaviors of the HNN are presented using bifurcation diagrams, dynamic maps, and Lyapunov exponent spectrums, considering different levels of crosstalk strengths. Simulation results also reveal that different crosstalk strengths can lead to wide-ranging nonlinear behaviors in the HNN systems.Keywords
Funding Information
- Fundamental Research Funds for the Central Universities (2019XKQYMS36)
This publication has 27 references indexed in Scilit:
- Numerical analyses and breadboard experiments of twin attractors in two-neuron-based non-autonomous Hopfield neural networkThe European Physical Journal Special Topics, 2018
- A review for dynamics in neuron and neuronal networkNonlinear Dynamics, 2017
- Using chaotic artificial neural networks to model memory in the brainCommunications in Nonlinear Science and Numerical Simulation, 2017
- A Hopfield Neural Network for Image Change DetectionIEEE Transactions on Neural Networks, 2006
- Hyperchaos in Hopfield-type neural networksNeurocomputing, 2005
- Is there chaos in the brain? II. Experimental evidence and related modelsComptes Rendus. Biologies, 2003
- The connections between the frustrated chaos and the intermittency chaos in small Hopfield networksNeural Networks, 2002
- VLSI Implementation of Neural NetworksInternational Journal of Neural Systems, 2000
- Economic load dispatch for piecewise quadratic cost function using Hopfield neural networkIEEE Transactions on Power Systems, 1993
- Neurons with graded response have collective computational properties like those of two-state neurons.Proceedings of the National Academy of Sciences, 1984