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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

The development of memristive device technologies has reached a level of maturity to enable the design of complex and large-scale hybrid memristive-CMOS neural processing systems. These systems offer promising solutions for implementing…

Emerging Technologies · Computer Science 2020-04-22 Elisabetta Chicca , Giacomo Indiveri

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

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

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

Processing-in-memory (PIM) solutions vastly accelerate systems by reducing data transfer between computation and memory. Memristors possess a unique property that enables storage and logic within the same device, which is exploited in the…

Hardware Architecture · Computer Science 2021-09-21 Orian Leitersdorf , Ronny Ronen , Shahar Kvatinsky

We present new computational building blocks based on memristive devices. These blocks, can be used to implement either supervised or unsupervised learning modules. This is achieved using a crosspoint architecture which is an efficient…

This paper proposes an innovative chaotic circuit based on Chua's oscillator. It combines traditional realization of a non-linear resistor in Chua's chaotic oscillator with a promising memristive circuitry. This mixed implementation…

Emerging Technologies · Computer Science 2018-05-22 Muratkhan Abdirash , Irina Dolzhikova , Alex Pappachen James

Memristive neural networks (MNNs), which use memristors as neurons or synapses, have become a hot research topic recently. However, most memristors are not compatible with mainstream integrated circuit technology and their stabilities in…

Emerging Technologies · Computer Science 2019-01-03 Zhiri Tang , Ruohua Zhu , Peng Lin , Jin He , Hao Wang , Qijun Huang , Sheng Chang , Qiming Ma

On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential. While algorithmic…

Emerging Technologies · Computer Science 2019-10-09 M. E. Fouda , F. Kurdahi , A. Eltawil , E. Neftci

Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently citepd as strong synapse candidates due to…

Neural and Evolutionary Computing · Computer Science 2015-09-02 David Howard , Larry Bull , Ben De Lacy Costello

In pursuit of neuromorphic (brain-inspired) devices, memristors (memory-resistors) have emerged as effective components for emulating neuronal circuitry. Here we formally define a class of Simple Volatile Memristors (SVMs) based on a simple…

Soft Condensed Matter · Physics 2024-09-20 T. M. Kamsma , R. van Roij , C. Spitoni

Memristors, as emerging nano-devices, offer promising performance and exhibit rich electrical dynamic behavior. Having already found success in applications such as neuromorphic and in-memory computing, researchers are now exploring their…

Cryptography and Security · Computer Science 2023-12-05 Ziang Chen , Li-Wei Chen , Xianyue Zhao , Kefeng Li , Heidemarie Schmidt , Ilia Polian , Nan Du

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

The modeling of conventional (deterministic) electronic circuits - ones consisting of transistors, resistors, capacitors, inductors, and other traditional electronic components - is a well-established subject. The cycle-to-cycle variability…

Emerging Technologies · Computer Science 2023-10-03 V. J. Dowling , V. A. Slipko , Y. V. Pershin

Memristive neuromorphic systems are designed to emulate human perception and cognition, where the memristor states represent essential historical information to perform both low-level and high-level tasks. However, current systems face…

Applied Physics · Physics 2024-09-17 Shengbo Wang , Cong Li , Tongming Pu , Jian Zhang , Weihao Ma , Luigi Occhipinti , Arokia Nathan , Shuo Gao

Cortical circuits exhibit intricate recurrent architectures that are remarkably similar across different brain areas. Such stereotyped structure suggests the existence of common computational principles. However, such principles have…

Neurons and Cognition · Quantitative Biology 2018-01-04 Rui Ponte Costa , Yannis M. Assael , Brendan Shillingford , Nando de Freitas , Tim P. Vogels

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 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

The emerging memristor crossbar array based computing circuits exhibit computing speeds and energy efficiency far surpassing those of traditional digital processors. This type of circuits can complete high-dimensional matrix operations in…

Signal Processing · Electrical Eng. & Systems 2025-06-05 Jia-Hui Bi , Shaoshi Yang , Sheng Chen , Ping Zhang