A memristive synapse control method to generate diversified multistructure chaotic attractors
Due to the synapse-like nonlinearity and memory characteristics, memristor is often used to
construct memristive neural networks with complex dynamical behaviors. However …
construct memristive neural networks with complex dynamical behaviors. However …
Memristor-coupled asymmetric neural networks: Bionic modeling, chaotic dynamics analysis and encryption application
With the rapid development of artificial intelligence, it has important theoretical and practical
significance to construct neural network models and study their dynamical behaviors. This …
significance to construct neural network models and study their dynamical behaviors. This …
Hidden bursting firings and bifurcation mechanisms in memristive neuron model with threshold electromagnetic induction
Memristors can be employed to mimic biological neural synapses or to describe
electromagnetic induction effects. To exhibit the threshold effect of electromagnetic …
electromagnetic induction effects. To exhibit the threshold effect of electromagnetic …
Dynamical effects of neuron activation gradient on Hopfield neural network: numerical analyses and hardware experiments
Hyperbolic tangent function, a bounded monotone differentiable function, is usually taken as
a neuron activation function, whose activation gradient, ie gain scaling parameter, can …
a neuron activation function, whose activation gradient, ie gain scaling parameter, can …
Dynamical analysis of a new chaotic system: asymmetric multistability, offset boosting control and circuit realization
C Ma, J Mou, L Xiong, S Banerjee, T Liu, X Han - Nonlinear Dynamics, 2021 - Springer
In this paper, a new four-dimensional dissipative chaotic system which can produce multiple
asymmetric attractors is designed and its dynamical behaviors are analyzed. The basin of …
asymmetric attractors is designed and its dynamical behaviors are analyzed. The basin of …
Coexisting firing patterns and phase synchronization in locally active memristor coupled neurons with HR and FN models
Z Li, H Zhou, M Wang, M Ma - Nonlinear Dynamics, 2021 - Springer
Local activity is regarded as the origin of complexity. In this study, a locally active memristor
with coexisting two stable pinched hysteresis loops and two local activity regions is …
with coexisting two stable pinched hysteresis loops and two local activity regions is …
A new class of Hopfield neural network with double memristive synapses and its DSP implementation
T Ma, J Mou, H Yan, Y Cao - The European Physical Journal Plus, 2022 - Springer
The nonlinear characteristics are studied in a new 4D Hopfield neural network model with
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
Coexisting multi-stable patterns in memristor synapse-coupled Hopfield neural network with two neurons
When possessing a potential difference between two neurons, an electromagnetic induction
current appears in the Hopfield neural network (HNN), which can be emulated by a flux …
current appears in the Hopfield neural network (HNN), which can be emulated by a flux …
Hidden extreme multistability with hyperchaos and transient chaos in a Hopfield neural network affected by electromagnetic radiation
Biological nervous system function is closely related to its dynamical behaviors, and some
dynamical phenomena observed in biological systems can be detected in the simplified …
dynamical phenomena observed in biological systems can be detected in the simplified …
Neural bursting and synchronization emulated by neural networks and circuits
Nowadays, research, modeling, simulation and realization of brain-like systems to
reproduce brain behaviors have become urgent requirements. In this paper, neural bursting …
reproduce brain behaviors have become urgent requirements. In this paper, neural bursting …