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The memristive device is one of the basic elements of novel, brain-inspired, fast, and energy-efficient information processing systems in which there is no separation between memorization and information analysis functions. Since the first…

We study transmission lines made of memory capacitive (memcapacitive) materials. The transmission properties of these lines can be adjusted on demand using an appropriate sequence of pulses. In particular, we demonstrate a pulse combination…

Mesoscale and Nanoscale Physics · Physics 2016-06-24 Y. V. Pershin , V. A. Slipko , M. Di Ventra

Memristors are passive elements that allow us to store information using a single element per bit. However, this is not the only utility of the memristor. Considering the physical chemical structure of the element used, the memristor can…

Emerging Technologies · Computer Science 2017-05-10 David Alejandro Trejo Pizzo

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

Human brain processes sensory information in real-time with extraordinary efficiency compared to the possibilities of current artificial computing systems. It operates as a complex nonlinear system, composed of interacting dynamic units -…

Emerging Technologies · Computer Science 2025-04-21 Manuel Escudero , Sabina Spiga , Stefano Brivio

Recently, in addition to the well-known resistor, capacitor and inductor, a fourth passive circuit element, named memristor, has been identified following theoretical predictions. The model example used in such case consisted in a nanoscale…

Mesoscale and Nanoscale Physics · Physics 2009-11-21 Yu. V. Pershin , M. Di Ventra

The advent of deep learning has resulted in a number of applications which have transformed the landscape of the research area in which it has been applied. However, with an increase in popularity, the complexity of classical deep neural…

Emerging Technologies · Computer Science 2022-08-24 Venkatesh Rammamoorthy , Geng Zhao , Bharathi Reddy , Ming-Yang Lin

Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…

Other Condensed Matter · Physics 2013-07-04 Siddharth Gaba , Patrick Sheridan , Jiantao Zhou , Shinhyun Choi , Wei Lu

Networks with memristive devices are a potential basis for the next generation of computing devices. They are also an important model system for basic science, from modeling nanoscale conductivity to providing insight into the…

Disordered Systems and Neural Networks · Physics 2025-07-01 Frank Barrows , Forrest C. Sheldon , Francesco Caravelli

An electrical analysis is performed for a memristor crossbar array integrated with operational amplifiers including the effects of parasitic or contact resistances. It is shown that the memristor crossbar array can act as a transfer matrix…

Instrumentation and Detectors · Physics 2010-04-02 Blaise Mouttet

We suggest electronic circuits with memristors (resistors with memory) that operate as memcapacitors (capacitors with memory) and meminductors (inductors with memory). Using a memristor emulator, the suggested circuits have been built and…

Instrumentation and Detectors · Physics 2014-11-20 Yuriy V. Pershin , Massimiliano Di Ventra

Memristors are an electronic device whose resistance depends on the voltage history that has been applied to its two terminals. Despite its clear advantage as a computational element, a suitable transport model is lacking for the special…

Emerging Technologies · Computer Science 2022-10-05 T. F. Tiotto , A. S. Goossens , A. E. Dima , C. Yakopcic , T. Banerjee , J. P. Borst , N. A. Taatgen

The increasing computational demands of deep learning models pose significant challenges for edge devices. To address this, we propose a memristor-based circuit design for MobileNetV3, specifically for image classification tasks. Our design…

Hardware Architecture · Computer Science 2025-04-04 Jiale Li , Zhihang Liu , Sean Longyu Ma , Chiu-Wing Sham , Chong Fu

Memristive systems were proposed in 1976 by Leon Chua and Sung Mo Kang as a model for 2-terminal passive nonlinear dynamical systems which exhibit memory effects. Such systems were originally shown to be relevant to the modeling of action…

Mesoscale and Nanoscale Physics · Physics 2010-12-24 Blaise Mouttet

The interplay between nonlinear dynamic systems and noise has proved to be of great relevance in several application areas. In this presentation, we focus on the areas of information transmission and storage. We review some recent results…

Other Condensed Matter · Physics 2017-11-22 P. I. Fierens , G. A. Patterson , A. A. García , D. F. Grosz

Highly accurate and predictive models of resistive switching devices are needed to enable future memory and logic design. Widely used is the memristive modeling approach considering resistive switches as dynamical systems. Here we introduce…

Emerging Technologies · Computer Science 2015-03-02 E. Linn , A. Siemon , R. Waser , S. Menzel

Memristive devices have drawn considerable research attention due to their potential applications in non-volatile memory and neuromorphic computing. The combination of resistive switching devices with light-responsive materials is…

Applied Physics · Physics 2020-09-22 Kamalakannan Ranganathan , Mor Feingenbaum , Ariel Ismach

Once referred to as the missing circuit component, memristor has come long way across to be recognized and taken as important to future circuit designs. The memristor due to its ability to memorize the state, switch between different…

Emerging Technologies · Computer Science 2016-12-07 Alex Pappachen James

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated. We have adopted a hysteretic graphene-based field emission structure as a…

Mesoscale and Nanoscale Physics · Physics 2017-01-17 Y. V. Pershin , S. N. Shevchenko

Neuromorphic devices, with their distinct advantages in energy efficiency and parallel processing, are pivotal in advancing artificial intelligence applications. Among these devices, memristive transistors have attracted significant…

Applied Physics · Physics 2024-11-08 Shengbo Wang , Jingfang Pei , Cong Li , Xuemeng Li , Li Tao , Arokia Nathan , Guohua Hu , Shuo Gao
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