Memristors can be employed to mimic biological neural synapses or describe electromagnetic induction effects. To exhibit the threshold effect of induction, this paper presents a flux-controlled memristor and examines its frequency-dependent pinched hysteresis loops. Using an current generated by replace external in 2-D Hindmarsh-Rose (HR) neuron model, 3-D memristive HR (mHR) model with global hidden oscillations is established corresponding numerical simulations are performed. It found that...

A memristive Chua's circuit regarded as a paradigm is reconsidered to exhibit its extreme multistability in this Letter. Memristor initial state‐dependent dynamics analysed and the coexistence of infinitely many attractors related memristor states revealed by numerical simulations simulations. The dynamical behaviour just reflects emergence circuit.

In this paper, from a new perspective of flux and charge, we present in-depth analyses two ideal memristor emulators the fifth-order memristive Chua's circuit constructed based on them. The constitutive flux-charge relations adopted are first formulated, their initial-dependent characteristics numerically revealed experimentally verified. Thereafter, with these relations, third-order dimensionality decreasing model for is constructed, in which five extra constant system parameters introduced...

Continuous memristor has been widely used in chaotic oscillating circuits and neuromorphic computing systems. However, discrete its coupling map have not noticed yet. This article presents a constructs general two-dimensional memristive model by the with an existing map. The pinched hysteresis loops of are demonstrated. Four examples maps provided their strength-relied initial-boosted complex dynamics investigated using numerical measures. evaluation results manifest that can enhance chaos...

The magnetic induction effects have been emulated by various continuous memristive models but they not successfully described a discrete model yet. To address this issue, article first constructs memristor and then presents Rulkov (m-Rulkov) neuron model. bifurcation routes of the m-Rulkov are declared detecting eigenvalue loci. Using numerical measures, we investigate complex dynamics shown in model, including regime transition behaviors, transient chaotic bursting regimes, hyperchaotic...

Regarding as a basic circuit component with special nonlinearity, memristor has been widely applied in chaotic circuits and neuromorphic circuits. However, discrete (DM) not received much attention, yet. To this end, paper reports general DM model its unified mapping model. Using the model, four representations of DMs are given their pinched hysteresis loops exhibited. Based on two-dimensional (2D) maps generated parameter-relied initials-relied behaviors explored using multiple numerical...

When chaotic sequences are used in engineering applications, their oscillating amplitudes need to be adjusted nondestructively. To accommodate this issue, article presents a simple 2-D sine map. It can not only generate the with high complexity, but also boost by switching initial states. show complex dynamics of map, investigates its control parameters-related dynamical behaviors and initials-boosted coexisting bifurcations using numerical methods. The results demonstrate that generated map...

Memristor synapse with activated synaptic plasticity can be taken as an adaptive connection weight. To demonstrate its kinetic effects, in this article, we present improved Hopfield neural network two memristive self-connection weights. The two-memristor-based (TM-HNN) has a plane equilibrium set related to two-memristor initial conditions and stability distributions are analyzed by nonzero roots of the eigenvalue polynomial. Afterward, parameter-related bifurcation behaviors investigated...

Analog circuit implementation of neuron model is an essential category neuromorphic since it can reproduce firing patterns and assist in exploring neuron-based applications. The models built by electrophysiological ion transport mechanism effectively mimic the patterns. However, they are rather difficult to implement on analog level because these involve complex exponential nonlinearities for characterizing channels. Thanks superiorities locally active memristor constructing artificial...

Detection of hidden dynamics is great value in model prediction and control engineering. To explore its effects methods the memristive network model, this paper presents a memristor synapse-driven ReLU-type Hopfield neural (MRHNN). The generalized Hamilton function derived from Helmholtz's theorem equilibrium points are analyzed. It found via numerical computations that because no existence equilibrium, MRHNN always unfolds dynamics, including bifurcation, mode transition, transient chaos,...

Since the electrical activities of neurons are closely related to complex electrophysiological environment in neuronal system, a novel three‐dimensional memristive Hindmarsh–Rose (HR) neuron model is presented this paper describe dynamics with electromagnetic induction. The proposed HR has no equilibrium point but can show hidden dynamical behaviors coexisting asymmetric attractors, which not been reported previous references for model. Mathematical based numerical simulations attractors...