Variability in resistive memories
Resistive memories are outstanding electron devices that have displayed a large potential in
a plethora of applications such as nonvolatile data storage, neuromorphic computing …
a plethora of applications such as nonvolatile data storage, neuromorphic computing …
Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron‐Style Models
Halide perovskites are at the forefront of active research in many applications, such as high
performance solar cells, photodetectors, and synapses and neurons for neuromorphic …
performance solar cells, photodetectors, and synapses and neurons for neuromorphic …
Hysteresis in memristors produces conduction inductance and conduction capacitance effects
Memristors are devices in which the conductance state can be alternately switched between
a high and a low value by means of a voltage scan. In general, systems involving a chemical …
a high and a low value by means of a voltage scan. In general, systems involving a chemical …
Experimental and modeling study of metal–insulator interfaces to control the electronic transport in single nanowire memristive devices
Memristive devices relying on redox-based resistive switching mechanisms represent
promising candidates for the development of novel computing paradigms beyond von …
promising candidates for the development of novel computing paradigms beyond von …
Spinel ferrites for resistive random access memory applications
Cutting edge science and technology needs high quality data storage devices for their
applications in artificial intelligence and digital industries. Resistive random access memory …
applications in artificial intelligence and digital industries. Resistive random access memory …
Simulation of bipolar-type resistive switching devices using a recursive approach to the dynamic memdiode model
Very often researchers in the field of resistive switching devices or memristors need to model
their experimental data using a compact representation without dealing with the …
their experimental data using a compact representation without dealing with the …
Synaptic response of fluidic nanopores: The connection of potentiation with hysteresis
Iontronic fluidic ionic/electronic components are emerging as promising elements for
artificial brain‐like computation systems. Nanopore ionic rectifiers can be operated as a …
artificial brain‐like computation systems. Nanopore ionic rectifiers can be operated as a …
Effects of the voltage ramp rate on the conduction characteristics of HfO2-based resistive switching devices
Memristive devices have shown a great potential for non-volatile memory circuits and
neuromorphic computing. For both applications it is essential to know the physical …
neuromorphic computing. For both applications it is essential to know the physical …
Fast fitting of the dynamic memdiode model to the conduction characteristics of RRAM devices using convolutional neural networks
In this paper, the use of Artificial Neural Networks (ANNs) in the form of Convolutional
Neural Networks (AlexNET) for the fast and energy-efficient fitting of the Dynamic Memdiode …
Neural Networks (AlexNET) for the fast and energy-efficient fitting of the Dynamic Memdiode …
Assessment of a universal logic gate and a full adder circuit based on cmos-memristor technology
The study of memristor-based digital logic circuits is a new approach in non-conventional
computation frameworks because of the memristor's properties, especially the ability to store …
computation frameworks because of the memristor's properties, especially the ability to store …