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

A memristive Hopfield neural network (MHNN) with a special activation gradient is proposed
by adding a suitable memristor to the Hopfield neural network (HNN) with a special …

In this paper, a new method for generating multi-scroll chaotic attractors via constructing a
compound hyperbolic tangent-cubic nonlinear function in canonical Chua's circuit is …

In this paper, we propose a hyperchaotic image encryption system based on particle swarm
optimization algorithm (PSO) and cellular automata (CA). Firstly, to improve the ability to …

Fractional calculus is closer to reality and has the same memory characteristics as
memristor. Therefore, a fractional-order multistable locally active memristor is proposed for …

Based on the special structure of variable-boostable chaotic system VB24, a quadratic flux-
controlled memristor is embedded for the construction of a 3D memristive chaotic system …

Memristor is widely used in various neural bionic models because of its excellent
characteristics in biological neural activity simulation. In this paper, a piecewise nonlinear …

This article studies the interesting dynamics of a small neural network with three neurons
under electromagnetic radiation. The electromagnetic radiation strength can change the …

Based on the two-dimensional (2D) discrete Rulkov model that is used to describe neuron
dynamics, this paper presents a continuous non-autonomous memristive Rulkov model. The …

This paper proposes a new memristor model and uses pinched hysteresis loops (PHL) to
prove the memristor characteristics of the model. Then, a new 6D fractional-order memristive …