Memristors for the Curious Outsiders

@article{Caravelli2018MemristorsFT,
  title={Memristors for the Curious Outsiders},
  author={Francesco Caravelli and Juan Pablo Carbajal},
  journal={ArXiv},
  year={2018},
  volume={abs/1812.03389}
}
We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to… Expand
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21 Citations
Background Citations
4
Methods Citations
2

21 Citations

Citation Type

Citation Type

Fully analog memristive circuits for optimization tasks: a comparison
TLDR
A Lyapunov function for the dynamics of Memristive circuits is introduced, and the effectiveness of memristors in minimizing the function is compared to widely used optimization software. Expand
Investigating a Discrete Model of Memristive Systems
Resistive-switching setups, which operate by controlled physical reconfiguration of the switching material, are extensively studied nowadays. These devices known as memristors are one of several… Expand
Asymptotic Behavior of Memristive Circuits
TLDR
It is shown that a polynomial Lyapunov function in the memory parameters exists for the case of DC controlled memristors, and an approximated but direct connection with the physics of disordered system and, in particular, of mean field spin glasses. Expand
Anisotropic MagnetoMemristance
The development of efficient beyond-von Neumann, bio-inspired, or unconventional computing hinges on the realization of novel devices that can be integrated into traditional circuitry. For this… Expand
Quantum Memristors in Frequency-Entangled Optical Fields
TLDR
It is shown that the characteristic hysteretic behavior of memristors can be reproduced when analyzing the response of the system with respect to the control, for different experimentally attainable states. Expand
Compensating Circuit to Reduce the Impact of Wire Resistance in a Memristor Crossbar-Based Perceptron Neural Network.
TLDR
A compensating circuit is proposed to reduce the impact of wire resistance in a memristor crossbar-based perceptron neural network and shows better recognition rate compared to the previous work when wire resistance is taken into account. Expand
Modeling and Analysis of a Three-Terminal-Memristor-Based Conservative Chaotic System
TLDR
In this paper, a three-terminal memristor is constructed and studied through changing dual-port output instead of one-port, which overcomes the challenge that a little bias will lead to the disappearance of conservative chaos. Expand
Reservoir Computing with Thin-film Ferromagnetic Devices
TLDR
It is shown, through simulation, that magnetic materials in thin-film geometries can realise reservoir computers with greater than or similar accuracy to digital recurrent neural networks and that neuromorphic hardware can be reduced in size by removing the need for discrete neural components and external processing. Expand
Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
TLDR
Simulation and experiment elucidate how collective memristive switching gives rise to long-range transport pathways, drastically altering the network’s global state via a discontinuous phase transition, thus demonstrating the potential for a neuromorphic advantage in information processing. Expand
Functional Oxides for Photoneuromorphic Engineering: Toward a Solar Brain
New device concepts and new computing principles are needed to balance our ever-growing appetite for data and information with the realization of the goals of increased energy efficiency, reduction… Expand
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