Resistance switching memory in perovskite oxides

The resistance switching behavior has recently attracted great attentions for its application as resistive random access memories (RRAMs) due to a variety of advantages such as simple structure, high-density, high-speed and low-power. As a leading storage media, the transition metal perovskite oxide owns the strong correlation of electrons and the stable crystal structure, which brings out multifunctionality such as ferroelectric, multiferroic, superconductor, and colossal magnetoresistance/electroresistance effect, etc. The existence of rich electronic phases, metal–insulator transition and the nonstoichiometric oxygen in perovskite oxide provides good platforms to insight into the resistive switching mechanisms.     

Dynamic behaviors of a class of memristor-based Hopfield networks

In this Letter, we analyze the dynamic behaviors for a class of memristor-based Hopfield networks. Some sufficient conditions are obtained which ensure the essential bound of solutions and global exponential stability of memristor-based Hopfield networks by using analysis approaches, and the criteria act as significant values for qualitative analysis of memristor-based Hopfield networks. Finally, a numerical example is given to show the effectiveness of our results.     

Multilevel resistive switching and synaptic behaviors in MnO-based memristor

Exploring new synaptic electronic devices that combine computing and memory is a promising strategy that fundamentally approaches intelligent machines. In this study, the multilevel resistive switching and synaptic behaviors of a MnO-based device is studied. The device is composed of Al/MnO/Ni sandwich structure, has stable resistance switching characteristics, has continuous nonvolatile memory state, can be used as electrically programmable and erasable analog memory. The gradual conductance modulation is realized by changing the compliance current and the maximum scanning voltage. The Al/MnO/Ni devices successfully mimic the basic functions of synapses, including the paired-pulse facilitation, spike-rate-dependent plasticity, excitatory postsynaptic current, short-term plasticity, long-term plasticity, and sike-timing-dependent plasticity.     

Global dynamics of diffusive Hindmarsh–Rose equations with memristors

Global dynamics of the diffusive Hindmarsh–Rose equations with memristors as a new proposed model for neuron dynamics are investigated in this paper. We prove the existence and regularity of a global attractor for the solution semiflow through uniform analytic estimates showing the higher-order dissipative property and the asymptotically compact characteristics of the solutions by the approach of Kolmogorov–Riesz theorem. The quantitative bounds of the regions containing this global attractor respectively in the state space and in the regular space are explicitly expressed by the model parameters.     

Fuzzy modeling and synchronization of different memristor-based chaotic circuits

This Letter is concerned with the problem of fuzzy modeling and synchronization of memristor-based Lorenz circuits with memristor-based Chua?s circuits. In this Letter, a memristor-based Lorenz circuit is set up, and illustrated by phase portraits and Lyapunov exponents. Furthermore, a new fuzzy model of memristor-based Lorenz circuit is presented to simulate and synchronize with the memristor-based Chua?s circuit. Through this new fuzzy model, two main advantages can be obtained as: (1) only two linear subsystems are needed; (2) fuzzy synchronization of these two different chaotic circuits with different numbers of nonlinear terms can be achieved with only two sets of gain K. Finally, numerical simulations are used to illustrate the effectiveness of these obtained results.     

Design of a memcapacitor emulator based on a memristor

Since Hewlett-Packard?s solid state implementation of a memristive system in 2008, a lot of research has begun to develop applications using this new component. As it is not available as a two terminal device yet, emulating circuits must be developed. Building on our previous work to develop an analog model of a memristor, a memcapacitor emulator is proposed in this Letter. This model can be realized by transforming a memristor emulator to a memcapacitor emulator. The characteristics of a memcapacitor are based on the theory proposed by L.O. Chua. The transformation process is described in detail in this Letter. Simulation and experimental results are given as well.     

MoTe2-based low energy consumption artificial synapse for neuromorphic behavior and decimal arithmetic

Two-dimensional material-based memristors have shown attractive research prospects as brain-like devices for neuromorphic computing. Among them, transition metal dichalcogenides–based memristors have proved to be one of the most promising competitors. In this work, a two-dimensional memristor based on MoTe₂ nanosheets was fabricated and demonstrated. The experimental results illustrate that the two-terminal synaptic based on the Ag/MoTe₂/ITO structure exhibits stable bipolar and non-volatile resistive switching characteristics attributed to the controllable formation and rupturing of silver conductive filaments. The device can be successively modulated by a pulse train with a minimum pulse width of 40 ns. More interestingly, the energy consumption of the device to complete one write event is only 74.2 pJ. In addition, biological synaptic behaviors, such as excitatory postsynaptic current gain properties, long-term potentiation (LTP)/long-term depression, spike-timing-dependent- plasticity, short-term plasticity, long-term potentiation (LTP), paired-pulse facilitation, post-tetanic potentiation, and learning-experimental behaviors were mimicked faithfully. Finally, the decimal arithmetic application was introduced to the device, and it is confirmed that addition and multiplication functions can be performed. Therefore, the artificial synapse based on MoTe₂ nanosheets not only exhibits the stable non-volatile resistive switching behavior but also facilitates the development of low-energy consumption neuromorphic computing chips based on transition metal dichalcogenides.     

Adaptive synchronization of memristor-based Chuaʼs circuits

In this Letter, a memristor-based Chua?s system is presented, and the chaotic behavior of this system is demonstrated by phase portraits. This Letter also deals with the problem of adaptive synchronization control of this chaotic system using the drive–response concept, and presents an adaptive control scheme for the synchronization of memristor-based Chua?s circuit, when the parameters of the drive system are fully unknown and different with those of the response system. The sufficient condition for the adaptive synchronization has been analyzed. Moreover, the controller design method is further extended to more general cases, where the physical plant contains parameter uncertainties, represented in either polytopic or structured frameworks. Numerical simulations are used to demonstrate these results.     

A general method to describe forgetting effect of memristors

Building suitable memristor models is essential when memristors are attractive to researchers and play a vital role in fields such as neuromorphic computing. The forgetting effect, which is usually used to mimic forgetting process of biological synapses, should be considered during the modeling process. Several models have been proposed to describe forgetting effect. However, they have some deficiencies in describing forgetting effect, such as boundary problems. In this paper, a general method is presented to resolve these problems. The method is suitable for models that employ an inner state to describe the change of resistance and use a window function to constrain the inner state (e.g., Chang's model, Chen's model, and Berdan's model). When the reason of forgetting effect is considered as dopant diffusion in previous models, the method determines the value of window function and the change rate of inner state according to the integrated result of dopant drift and dopant diffusion. Simulation results indicate that the issues of previous models are solved when the proposed method is applied in these models.