相关论文: Temperature control of diffusive memristor hystere…
Diffusive memristors owing to their ability to produce current spiking when a constant or slowly changing voltage is applied are competitive candidates for the development of artificial electronic neurons. These artificial neurons can be…
Advanced neural interfaces mediate a bio-electronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading…
Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…
The electrical properties and performance characteristics of niobium dioxide (NbO$_\mathrm{2}$)-based memristive devices are examined at cryogenic temperatures. Sub-stoichiometric Nb$_\mathrm{2}$O$_\mathrm{5}$ was deposited via magnetron…
Memristive devices are commonly benchmarked by the multi-level programmability of their resistance states. Neural networks utilizing memristor crossbar arrays as synaptic layers largely rely on this feature. However, the dynamical…
We present the effect of temperature on the switching characteristics of a bistable nonlinear nanomechanical beam. At MHz-range frequencies, we find that it is possible to controllably change the state of the system between two stable…
In this theoretical study, we focus on the high-frequency response of the electrothermal NbO2-Mott threshold switch, a real-world electronic device, which has been proved to be relevant in several applications and is classified as a…
Memristors have been suggested as neuromorphic computing elements. Spike-time dependent plasticity and the Hodgkin-Huxley model of the neuron have both been modelled effectively by memristor theory. The d.c. response of the memristor is a…
Nanoscale metal oxide memristors have potential in the development of brain-inspired computing systems that are scalable and efficient1-3. In such systems, memristors represent the native electronic analogues of the biological synapses.…
It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive…
In many cases, the behavior of physical memristive devices can be relatively well captured by using a single internal state variable. This study investigates the low-power control of first-order memristive devices to derive the most…
Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tuneable conductivity properties enable the imitation of synaptic behaviour. Multipore nanofluidic memristors have shown their…
In this paper, we build a general modelling framework for memristors, suitable for the simulation of event-based systems such as hardware spiking neural networks, and more generally, neuromorphic computing systems composed of three…
The memristor is a device whose resistance changes depending on the polarity and magnitude of a voltage applied to the device's terminals. We design a minimalistic model of a regular network of memristors using structurally-dynamic cellular…
The memristive device is one of the basic elements of novel, brain-inspired, fast, and energy-efficient information processing systems in which there is no separation between memorization and information analysis functions. Since the first…
Memristive devices have been considered promising candidates for nature-inspired computing and in-memory information processing. However, experimental devices developed to date typically show significant variability and function at…
The computational efficiency of the human brain is believed to stem from the parallel information processing capability of neurons with integrated storage in synaptic interconnections programmed by local spike triggered learning rules such…
Strongly correlated insulators, such as Mott or charge-transfer insulators, exhibit a strong temperature dependence in their resistivity. Consequently, self-heating effects can lead to electrothermal instabilities in planar thin film…
Active memristor elements, also called neuristors, are self-oscillating devices that are very good approximations to biological neuronal functionality and are crucial to the development of low-power neuromorphic hardware. Materials that…
Memristors stand out as promising components in the landscape of memory and computing. Memristors are generally defined by a conductance equation containing a state variable that imparts a memory effect. The current-voltage cycling causes…