The study of dynamics on artificial neurons and neuronal networks is of great significance to
understand brain functions and develop neuromorphic systems. Recently, memristive …

Since the Lorenz chaotic system was discovered in 1963, the construction of chaotic
systems with complex dynamics has been a research hotspot in the field of chaos. Recently …

Memristor is an ideal electronic device used as an artificial nerve synapse due to its unique
memory function. This article presents a design of a new Hopfield neural network (HNN) that …

Memristors are well suited as artificial nerve synapses owing to its unique memory function.
This paper establishes a novel flux-controlled memristor model using hyperbolic function …

Fractional-order differentiation (FOD) can record information from the past, present, and
future. Compared with integer-order systems, FOD systems have higher complexity and …

Memristors have recently demonstrated great promise in constructing memristive neural
networks with complex dynamics. This article proposes a memristive Hopfield neural …

Due to the synapse-like nonlinearity and memory characteristics, memristor is often used to
construct memristive neural networks with complex dynamical behaviors. However …

Because of the nonlinearity and memory, memristors are the most suitable electrical
component for simulating synapses. A novel local active and nonvolatile memristor is …

The number of attractors in a memristor-based multiscroll Hopfield Neural Network (HNN) is
typically coupled with the number of polynomials, which leads to a coupling between the …

Memristors are widely considered to be promising candidates to mimic biological synapses.
In this paper, by introducing a non-ideal flux-controlled memristor model into a Hopfield …