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Related papers: Circuit elements with memory: memristors, memcapac…

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This paper presents a memristor-based compute-in-memory hardware accelerator for on-chip training and inference, focusing on its accuracy and efficiency against device variations, conductance errors, and input noise. Utilizing realistic…

Neural and Evolutionary Computing · Computer Science 2024-08-28 M. Reza Eslami , Dhiman Biswas , Soheib Takhtardeshir , Sarah S. Sharif , Yaser M. Banad

Practical memristor came into picture just few years back and instantly became the topic of interest for researchers and scientists. Memristor is the fourth basic two-terminal passive circuit element apart from well known resistor,…

Emerging Technologies · Computer Science 2015-06-23 Tejinder Singh

Memtranstor that correlates charge and magnetic flux via nonlinear magnetoelectric effects has a great potential in developing next-generation nonvolatile devices. In addition to multi-level nonvolatile memory, we demonstrate here that…

Emerging Technologies · Computer Science 2017-01-04 Jianxin Shen , Dashan Shang , Yisheng Chai , Yue Wang , Junzhuang Cong , Shipeng Shen , Liqin Yan , Wenhong Wang , Young Sun

The simplest electronic circuit with a memristor was recently proposed. Chaotic attractors solution to this memristive circuit are topologically characterized and compared to Rossler-like attractors.

Dynamical Systems · Mathematics 2014-08-19 Jean-Marc Ginoux , Christophe Letellier , Leon L. O. Chua

The smart integrated systems of tomorrow would demand a combination of micromechanical components and traditional electronics. On-chip solutions will be the ultimate goal. One way of making such systems is to implement the mechanical parts…

Other Computer Science · Computer Science 2008-02-22 O. Soeraasen , J. E. Ramstad

In 1976, Leon Chua showed that a thermistor can be modeled as a memristive device. Starting from this statement we designed a circuit that has four circuit elements: a linear passive inductor, a linear passive capacitor, a nonlinear…

Emerging non-volatile memory (NVM), or memristive, devices promise energy-efficient realization of deep learning, when efficiently integrated with mixed-signal integrated circuits on a CMOS substrate. Even though several algorithmic…

Neural and Evolutionary Computing · Computer Science 2018-04-23 Vishal Saxena , Xinyu Wu , Kehan Zhu

We suggest a novel methodology to obtain a digital representation of analog signals and to perform its back-conversion using memristive devices. In the proposed converters, the same memristive systems are used for two purposes: as elements…

Instrumentation and Detectors · Physics 2012-07-04 Y. V. Pershin , E. Sazonov , M. Di Ventra

Capacitors are typically connected together in one of two configurations: either in series, or in parallel. Here we study a capacitor-within-capacitor (CWC). Simulations and experiments indicate that the overall capacitance of the…

General Physics · Physics 2019-07-09 Haim Grebel

In the last decade, a 2-terminal passive circuit element called a memristor has been developed for non-volatile resistive random access memory and has more recently shown promise for neuromorphic computing. Compared to flash memory,…

There are three theoretical models which purport to relate experimentally-measurable or fabrication-controllable device properties to the memristor's operation: 1. Strukov et al's phenomenological model; 2. Georgiou et al's Bernoulli…

Materials Science · Physics 2013-12-17 Ella M. Gale , Benjamin de Lacy Costello , Andrew Adamatzky

A circuit-field problem is considered. A resistor conducting a constant current is argued to be associated with electromagnetic energy accumulated in the surrounded space, though contrary to the case of an inductor or a capacitor, this…

General Physics · Physics 2010-06-23 Emanuel Gluskin

We show that memcapacitive (memory capacitive) systems can be used as synapses in artificial neural networks. As an example of our approach, we discuss the architecture of an integrate-and-fire neural network based on memcapacitive…

Disordered Systems and Neural Networks · Physics 2016-06-24 Y. V. Pershin , M. Di Ventra

Recent results in adaptive matter revived the interest in the implementation of novel devices able to perform brain-like operations. Here we introduce a training algorithm for a memristor network which is inspired in previous work on…

Emerging Technologies · Computer Science 2022-05-13 Juan Pablo Carbajal , Daniel Alejandro Martin , Dante Renato Chialvo

We suggest a realization of a bistable non-volatile memory capacitor (memcapacitor). Its design utilizes a strained elastic membrane as a plate of a parallel-plate capacitor. The applied stress generates low and high capacitance…

Mesoscale and Nanoscale Physics · Physics 2011-09-29 J. Martinez-Rincon , Y. V. Pershin

In 1971, Chua defined an ideal memristor that links charge q and flux phi. In this work, we demonstrated that the direct interaction between physical charge q and physical flux phi is memristive by nature in terms of a time-invariant phi-q…

Mesoscale and Nanoscale Physics · Physics 2022-03-22 Frank Zhigang Wang

Memristors have attracted interest as neuromorphic computation elements because they show promise in enabling efficient hardware implementations of artificial neurons and synapses. We performed measurements on interface-type memristors to…

Emerging Technologies · Computer Science 2021-01-07 Thomas F. Tiotto , Anouk S. Goossens , Jelmer P. Borst , Tamalika Banerjee , Niels A. Taatgen

The unprecedented advancement of artificial intelligence has placed immense demands on computing hardware, but traditional silicon-based semiconductor technologies are approaching their physical and economic limit, prompting the exploration…

Emerging Technologies · Computer Science 2025-01-23 Mingrui Jiang , Yichun Xu , Zefan Li , Can Li

Dynamic reconfiguration of charge carriers in confined ion-channels under electrical stimulation produces memory effects, where the internal resistance depends on history of the electric field. Vermiculite nanofluidic devices harness this…

Amorphous insulators have localized wave functions that decay with the distance $r$ following exp($-r/\zeta$). Since nanoscale conduction is not excluded at $r<\zeta$, one may use amorphous insulators and take advantage of their size effect…

Mesoscale and Nanoscale Physics · Physics 2019-02-21 Yang Lu , I-Wei Chen