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Neuromorphic circuits mimic partial functionalities of brain in a bio-inspired information processing sense in order to achieve similar efficiencies as biological systems. While there are common mathematical models for neurons, which can be…

Emerging Technologies · Computer Science 2017-09-26 Enver Solan , Karlheinz Ochs

Memristors, when utilized as electronic components in circuits, can offer opportunities for the implementation of novel reconfigurable electronics. While they have been used in large arrays, studies in ensembles of devices are comparatively…

Applied Physics · Physics 2022-04-06 Vasileios Manouras , Spyros Stathopoulos , Alex Serb , Themis Prodromakis

Memristors are promising devices for scalable and low power, in-memory computing to improve the energy efficiency of a rising computational demand. The crossbar array architecture with memristors is used for vector matrix multiplication…

Emerging Technologies · Computer Science 2025-05-20 Neethu Kuriakose , Arun Ashok , Christian Grewing , André Zambanini , Stefan van Waasen

This paper describes a new memristor crossbar architecture that is proposed for use in a high density cache design. This design has less than 10% of the write energy consumption than a simple memristor crossbar. Also, it has up to 4 times…

Hardware Architecture · Computer Science 2013-04-10 Chris Yakopcic , Tarek M. Taha

Emerging memristor-based array architectures have been effectively employed in non-volatile memories and neuromorphic computing systems due to their density, scalability and capability of storing information. Nonetheless, to demonstrate a…

Emerging Technologies · Computer Science 2022-05-18 Jiawei Shen , Andrea Mifsud , Lijie Xie , Abdulaziz Alshaya , Christos Papavassiliou

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

Memristive circuit elements constitute a cornerstone for novel electronic applications, such as neuromorphic computing, called to revolutionize information technologies. By definition, memristors are sensitive to the history of electrical…

We investigate the Fourier transform of the current through a memristor when the applied-voltage frequency is smaller than the characteristic memristor frequency, and the memristor shows hysteresis in the current-voltage plane. We find that…

Mesoscale and Nanoscale Physics · Physics 2013-01-08 Yogesh N. Joglekar , Natalia Meijome

The memory resistor abbreviated memristor was a harmless postulate in 1971. In the decade since 2008, a device claiming to be the missing memristor is on the prowl, seeking recognition as a fundamental circuit element, sometimes wanting…

Emerging Technologies · Computer Science 2018-08-21 Isaac Abraham

A current problem in semiconductor spin-based electronics is the difficulty of experimentally expressing the effect of spin-polarized current in electrical circuit measurements. We present a theoretical solution with the principle of…

Mesoscale and Nanoscale Physics · Physics 2008-02-20 Hanan Dery , Lukasz Cywinski , Lu J. Sham

The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find…

Neural and Evolutionary Computing · Computer Science 2022-10-28 Udit Kumar Agarwal , Shikhar Makhija , Varun Tripathi , Kunwar Singh

Passive crossbar arrays based upon memristive devices, at crosspoints, hold great promise for the future high-density and non-volatile memories. The most significant challenge facing memristive device based crossbars today is the problem of…

Emerging Technologies · Computer Science 2015-07-09 Yansong Gao , Omid Kavehei , Damith C. Ranasinghe , Said F. Al-Sarawi , Derek Abbott

Monolithic three-dimensional integration of memory and logic circuits could dramatically improve performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration,…

Emerging Technologies · Computer Science 2015-09-11 Gina C. Adam , Brian D. Hoskins , Mirko Prezioso , Dmitri B. Strukov

Memristive devices whose resistance can be hysteretically switched by electric field or current are intensely pursued both for fundamental interest as well as potential applications in neuromorphic computing and phase-change memory. When…

A memristor, a two-terminal nanodevice, has garnered substantial attention in recent years due to its distinctive properties and versatile applications. These nanoscale components, characterized by their simplicity of manufacture,…

Applied Physics · Physics 2025-02-20 Nikolaos Vasileiadis , Georgios Ch Sirakoulis , Panagiotis Dimitrakis

Reasoned by its dynamical behavior, the memristor enables a lot of new applications in analog circuit design. Since some realizations are shown (e.g. 2007 by Hewlett Packard), the development of applications with memristors becomes more and…

Materials Science · Physics 2013-02-19 Oliver Pabst , Torsten Schmidt

Switching uniformity, as a major challenge, hinders the practical implementation of \ac{RRAM} in memory application. Operating \ac{RRAM} in current mode, is proposed as an efficient method to improve programming schemes accuracy within the…

Emerging Technologies · Computer Science 2026-03-02 Bojian Zhang , Paolo Gibertini , Meysam Akbari , Erika Covi

Memristor crossbar arrays have emerged as a key component for next-generation non-volatile memories, artificial neural networks, and analog in-memory computing (IMC) systems. By minimizing data transfer between the processor and memory,…

Emerging Technologies · Computer Science 2026-01-16 Shah Zayed Riam , Zhenlin Pei , Kyle Mooney , Chenyun Pan , Na Gong , Jinhui Wang

Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by…

Motivated by advantages of current-mode design, this brief contribution explores the implementation of weight matrices in neuromemristive systems via current-mode memristor crossbar circuits. After deriving theoretical results for the range…

Machine Learning · Statistics 2017-07-19 Cory Merkel