Stochastic memory: Memory enhancement due to noise

Stotland, Alexander; Ventra, Massimiliano Di

doi:10.1103/physreve.85.011116

Cited by 70 publications

(65 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Introducing linear functions as discussed in this paper allows one to obtain optimal conditions for any device models of memristors. Also, the excellent agreement between simulation 33 and experiment 34 has been reported in the scheme of stochastic resonance. Modulators using memristors have been verified in SPICE simulations.…”

Section: Optimal Condition Of External Voltage Sourcesupporting

confidence: 62%

Optimal condition of memristance enhancement circuit using external voltage source

2014

View full text Add to dashboard Cite

Memristor provides nonlinear response in the current-voltage characteristic and the memristance is modulated using an external voltage source. We point out by solving nonlinear equations that an optimal condition of the external voltage source exists for maximizing the memristance in such modulation scheme. We introduce a linear function to describe the nonlinear time response and derive an important design guideline; a constant ratio of the frequency to the amplitude of the external voltage source maximizes the memristance. The analysis completely accounts for the memristance behavior.

show abstract

Section: Optimal Condition Of External Voltage Sourcesupporting

confidence: 62%

Optimal condition of memristance enhancement circuit using external voltage source

2014

View full text Add to dashboard Cite

show abstract

“…Several reports [47,48] have already shown the importance of noise in the response of memristive devices to the external driving field. However, the approach used is limited to the case of a bistable system and must be extended to the multi-stable energetic profile describing the real situation more correctly.…”

Section: Noise-induced Phenomenamentioning

confidence: 99%

Field‐ and irradiation‐induced phenomena in memristive nanomaterials

Mikhaylov

Gryaznov

Belov

et al. 2016

Phys. Status Solidi C

View full text Add to dashboard Cite

The breakthrough in electronics and information technology is anticipated by the development of emerging memory and logic devices, artificial neural networks and brain-inspired systems on the basis of memristive nano-materials represented, in a particular case, by a simple 'metal-insulator-metal' (MIM) thin-film structure. The present article is focused on the comparative analysis of MIM devices based on oxides with dominating ionic (ZrOx, HfOx) and covalent (SiOx, GeOx) bonding of various composition and geometry deposited by magnetron sputtering. The studied memristive devices demonstrate reproducible change in their resistance (resistive switching - RS) originated from the formation and rupture of conductive pathways (filaments) in oxide films due to the electric-field-driven migration of oxygen vacancies and/or mobile oxygen ions. It is shown that, for both ionic and covalent oxides under study, the RS behaviour depends only weakly on the oxide film composition and thickness, device geometry (down to a device size of about 20x20 mu m(2)). The devices under study are found to be tolerant to ion irradiation that reproduces the effect of extreme fluences of high-energy protons and fast neutrons. This common behaviour of RS is explained by the localized nature of the redox processes in a nanoscale switching oxide volume. Adaptive (synaptic) change of resistive states of memristive devices is demonstrated under the action of single or repeated electrical pulses, as well as in a simple model of coupled (synchronized) neuron-like generators. It is concluded that the noise-induced phenomena cannot be neglected in the consideration of a memristive device as a nonlinear system. The dynamic response of a memristive device to periodic signals of complex waveform can be predicted and tailored from the viewpoint of stochastic resonance concept. (C) 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei

show abstract

“…18 It is to note that such systems are expected to reveal improved noise resistance. 19,20 Organic memristive devices (our basic element for the adaptive networks) is formed by a heterojunction of conducting polymer and solid electrolyte, in particular, polyaniline (PANI) and polyethylene oxide (PEO) doped with lithium salts. 9 Thus, the formed supported network must contain these materials distributed in a stochastic manner with a statistical probability of forming the desirable contacts of two mentioned materials.…”

mentioning

confidence: 99%

Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning

2015

View full text Add to dashboard Cite

Stochastic networks of memristive devices were fabricated using a sponge as a skeleton material. Cyclic voltage-current characteristics, measured on the network, revealed properties, similar to the organic memristive device with deterministic architecture. Application of the external training resulted in the adaptation of the network electrical properties. The system revealed an improved stability with respect to the networks, composed from polymer fibers.

show abstract

Stochastic memory: Memory enhancement due to noise

Cited by 70 publications

References 29 publications

Optimal condition of memristance enhancement circuit using external voltage source

Optimal condition of memristance enhancement circuit using external voltage source

Field‐ and irradiation‐induced phenomena in memristive nanomaterials

Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning

Contact Info

Product

Resources

About