Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is
suitable for encryption applications. In order to ensure the information security of the medical …

Memristive electromagnetic induction effect has been widely explored in bi-neuron network
with homogeneous neurons, but rarely in bi-neuron network with heterogeneous ones. This …

Spiking firing patterns and their hardware implementation can assist us in exploring spike-
based applications. The classical Hodgkin–Huxley circuit can generate spiking firing …

Electromagnetic induction plays a vital role in impacting the neuron dynamics, since the
electromagnetic induction is triggered alongside with the complex interaction of membrane …

Designing a low-dimensional discrete map to generate chaotic sequence with the properties
of high randomness and without chaos degradation is an attractive but challenging issue …

In order to enrich the dynamic behaviors of discrete neuron models and more effectively
mimic biological neural networks, this paper proposes a bistable locally active discrete …

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 …

Extreme multistable systems can show vibrant dynamical properties and infinitely many
coexisting attractors generated by changing the initial conditions while the system and its …

Memristive neurons and memristive neural networks constructed based on memristors have
important research significance for revealing the mystery of the brain. This paper proposes a …

Fractional-order chaotic systems are widely used in the field of encryption because of its
initial value sensitivity and historical memory. In this paper, the fractional-order definition of …