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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

A simple and unambiguous test has been recently suggested [J. Phys. D: Applied Physics, 52, 01LT01 (2018)] to check experimentally if a resistor with memory is indeed a memristor, namely a resistor whose resistance depends only on the…

Mesoscale and Nanoscale Physics · Physics 2023-10-03 Y. V. Pershin , J. Kim , T. Datta , M. Di Ventra

Current advances in emerging memory technologies enable novel and unconventional computing architectures for high-performance and low-power electronic systems, capable of carrying out massively parallel operations at the edge. One emerging…

Emerging Technologies · Computer Science 2018-10-12 Georgios Papandroulidakis , Alexantrou Serb , Ali Khiat , Geoff V. Merrett , Themistoklis Prodromakis

Analog memory is of great importance in neurocomputing technologies field, but still remains difficult to implement. With emergence of memristors in VLSI technologies the idea of designing scalable analog data storage elements finds its…

Emerging Technologies · Computer Science 2017-09-14 Aidana Irmanova , Alex Pappachen James

Memristors are novel non volatile devices that manage to combine storing and processing capabilities in the same physical place.Their nanoscale dimensions and low power consumption enable the further design of various nanoelectronic…

Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…

Emerging Technologies · Computer Science 2012-12-17 Victor Erokhin , Gerard David Howard , Andrew Adamatzky

Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing…

Emerging Technologies · Computer Science 2017-11-08 Giacomo Indiveri , Bernabe Linares-Barranco , Robert Legenstein , George Deligeorgis , Themistoklis Prodromakis

Memory circuit elements, namely memristive, memcapacitive and meminductive systems, are gaining considerable attention due to their ubiquity and use in diverse areas of science and technology. Their modeling within the most widely used…

Computational Physics · Physics 2016-06-24 D. Biolek , M. Di Ventra , Y. V. Pershin

In almost all of the currently working circuits, especially in analog circuits implementing signal processing applications, basic arithmetic operations such as multiplication, addition, subtraction and division are performed on values which…

Hardware Architecture · Computer Science 2010-09-03 Farnood Merrikh-Bayat , Saeed Bagheri Shouraki

Memristor networks are capable of low-power and massive parallel processing and information storage. Moreover, they have presented the ability to apply for a vast number of intelligent data analysis applications targeting mobile edge…

The ever-increasing amount of data from ubiquitous smart devices fosters data-centric and cognitive algorithms. Traditional digital computer systems have separate logic and memory units, resulting in a huge delay and energy cost for…

Applied Physics · Physics 2025-03-17 Qiming Shao , Zhongrui Wang , Yan Zhou , Shunsuke Fukami , Damien Querlioz , Leon O. Chua

The class of memory circuit elements which comprises memristive, memcapacitive, and meminductive systems, is gaining considerable attention in a broad range of disciplines. This is due to the enormous flexibility these elements provide in…

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

In 1971 the memristor was originally postulated as a new non-linear circuit element relating the time integrals of current and voltage. More recently researchers at HPLabs have linked the theoretical memristor concept to resistance…

Mesoscale and Nanoscale Physics · Physics 2010-03-16 Blaise Mouttet

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

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…

In this paper we revisit the memristor concept within circuit theory. We start from the definition of the basic circuit elements, then we introduce the original formulation of the memristor concept and summarize some of the controversies on…

Systems and Control · Electrical Eng. & Systems 2021-02-24 Bernardo Tellini , Mauro Bologna , Kristopher J. Chandia , Massimo Macucci

Memristors, initially introduced in the 1970s, have received increased attention upon successful synthesis in 2008. Considerable work has been done on modeling and applications in specific areas, however, very little is known on the…

Optimization and Control · Mathematics 2014-08-01 Gourav Saha , Ramkrishna Pasumarthy , Prathamesh Khatavkar

Quantum computer technology harnesses the features of quantum physics for revolutionizing information processing and computing. As such, quantum computers use physical quantum gates that process information unitarily, even though the final…

In this paper, we present a resistive switching memristor cell for implementing universal logic gates. The cell has a weighted control input whose resistance is set based on a control signal that generalizes the operational regime from NAND…

Emerging Technologies · Computer Science 2016-09-19 Akshay Kumar Maan , Alex Pappachen James

Memristive devices hold promise to improve the scale and efficiency of machine learning and neuromorphic hardware, thanks to their compact size, low power consumption, and the ability to perform matrix multiplications in constant time.…

Emerging Technologies · Computer Science 2024-08-14 Zhenming Yu , Ming-Jay Yang , Jan Finkbeiner , Sebastian Siegel , John Paul Strachan , Emre Neftci