# Memristor Networks

@inproceedings{Adamatzky2014MemristorN,
title={Memristor Networks},
author={A. Adamatzky and L. Chua},
booktitle={Springer International Publishing},
year={2014}
}
• Published in
Springer International…
2014
• Computer Science
Using memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the memristor is of great pragmatic usefulness. Potential unique applications of memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits and programmable electronics. Memristor Networks focuses on the design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many… Expand
83 Citations
Sensitivity analysis of memristors based on emulation techniques
• Computer Science
• 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS)
• 2016
This work uses memristor emulators, based on the wave digital method, for sensitivity analysis, and gets a reproducible investigation method, which can be used in real circuits, before fabricating the real device. Expand
Switching Synchronization and Metastable States in 1D Memristive Networks
• Computer Science
• Handbook of Memristor Networks
• 2019
It is shown that metastable transmission lines composed of metastable memristive circuits can be used to transfer the information from one space location to another and the triad of memory networks functionalities in their 1D networks: information processing, storage and transfer. Expand
Experimental verification of a memristive neural network
• Computer Science
• 2018
An electronic circuit able to emulate the behavior of a neural network based on memristive synapses is presented, built with two flux-controlled floating memristor emulator circuits operating at high frequency and two passive resistors. Expand
Experimental Study of Artificial Neural Networks Using a Digital Memristor Simulator
• Computer Science, Medicine
• IEEE Transactions on Neural Networks and Learning Systems
• 2018
A fully digital implementation of a memristor hardware (HW) simulator, as the core of an emulator, based on a behavioral model of voltage-controlled threshold-type bipolar memristors, which demonstrates very good matching with the mathematical model on which it is based. Expand
Memristors as Candidates for Replacing Digital Potentiometers in Electric Circuits
• Computer Science
• 2021
This paper has analyzed and implemented tunable circuits such as a voltage divider, an inverting amplifier, a high-pass filter, and a phase shifter, and verified that a memristor has equal or better characteristics than a digital potentiometer. Expand
Memristor Models for Machine Learning
• Medicine, Computer Science
• Neural Computation
• 2015
The results indicate that device variability, increasingly causing problems in traditional computer design, is an asset in the context of reservoir computing, and proposes two different ways to incorporate it into memristor simulation models. Expand
Memristor and Inverse Memristor: Modeling, Implementation and Experiments
• Physics
• 2017
Pinched hysteresis is considered to be a signature of the existence of memristive behavior. However, this is not completely accurate. In this chapter, we are discussing a general equation taking intoExpand
Stochastic Memristive Interface between Electronic FitzHugh-Nagumo Neurons
The dynamics of memristive device in response to neuron-like signals and coupling electronic neurons via memristive device has been investigated theoretically and experimentally. The simplestExpand
High-frequency memristive synapses
• Computer Science
• 2017 IEEE 8th Latin American Symposium on Circuits & Systems (LASCAS)
• 2017
An analysis of the memristor characteristics in order to obtain a suitable synaptic response is described, showing symmetrical synaptic weighting when the k parameter is close to its maximum value. Expand
Hybrid memristor/RTD structure-based cellular neural networks with applications in image processing
• Computer Science
• Neural Computing and Applications
• 2013
Since both the memristor and the resonant tunneling diode are nanoscale, the size of the network circuits can be greatly reduced, and the integration density of the system will be significantly improved. Expand

#### References

SHOWING 1-10 OF 109 REFERENCES
The elusive memristor: properties of basic electrical circuits
• Physics
• 2009
We present an introduction to and a tutorial on the properties of the recently discovered ideal circuit element, a memristor. By definition, a memristor M relates the charge q and the magnetic flux !Expand
A ferroelectric memristor.
It is demonstrated that voltage-controlled domain configurations in ferroelectric tunnel barriers yield memristive behaviour with resistance variations exceeding two orders of magnitude and a 10 ns operation speed. Expand
A hybrid nanomemristor/transistor logic circuit capable of self-programming
The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. Expand
Memristive devices and systems
• Engineering
• Proceedings of the IEEE
• 1976
A broad generalization of memristors--a recently postulated circuit element--to an interesting class of nonlinear dynamical systems called memristive systems is introduced. These systems areExpand
Self-organized computation with unreliable, memristive nanodevices
Nanodevices have terrible properties for building Boolean logic systems: high defect rates, high variability, high death rates, drift, and (for the most part) only two terminals. Economical assemblyExpand
Simulation of a memristor-based spiking neural network immune to device variations
• Computer Science
• The 2011 International Joint Conference on Neural Networks
• 2011
System level simulations on a textbook case show that performance can compare with traditional supervised networks of similar complexity and show the system can retain functionality with extreme variations of various memristors' parameters, thanks to the robustness of the scheme, its unsupervised nature, and the power of homeostasis. Expand
Nanoscale memristor device as synapse in neuromorphic systems.
• Materials Science, Medicine
• Nano letters
• 2010
A nanoscale silicon-based memristor device is experimentally demonstrated and it is shown that a hybrid system composed of complementary metal-oxide semiconductor neurons and Memristor synapses can support important synaptic functions such as spike timing dependent plasticity. Expand
Memristor-The missing circuit element
A new two-terminal circuit element-called the memristorcharacterized by a relationship between the charge q(t)\equiv \int_{-\infty}^{t} i(\tau) d \tau and the flux-linkage \varphi(t)\equiv \int_{-Expand
Memristive switching mechanism for metal/oxide/metal nanodevices.
• Materials Science, Medicine
• Nature nanotechnology
• 2008
Experimental evidence is provided to support this general model of memristive electrical switching in oxide systems, and micro- and nanoscale TiO2 junction devices with platinum electrodes that exhibit fast bipolar nonvolatile switching are built. Expand
Spike-timing-dependent learning in memristive nanodevices
• G. Snider
• Computer Science
• 2008 IEEE International Symposium on Nanoscale Architectures
• 2008
The key ideas are to factor out two synaptic state variables to pre- and post-synaptic neurons and to separate computational communication from learning by time-division multiplexing of pulse-width-modulated signals through synapses. Expand