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Reversible bipolar nano-switches that can be set and read electronically in a solid-state two-terminal device are very promising for applications. We have performed molecular-dynamics simulations that mimic systems with oxygen vacancies…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 S. E. Savel'ev , A. S. Alexandrov , A. M. Bratkovsky , R. Stanley Williams

Several devices exhibiting memory effects have shown up in nonlinear circuit theory in recent years. Among others, these circuit elements include Chua's memristors, as well as memcapacitors and meminductors. These and other related devices…

Dynamical Systems · Mathematics 2013-07-09 Ricardo Riaza

A memristive device is a novel passive device, which is essentially a resistor with memory. This device can be utilized for novel technical applications like neuromorphic computation. In this paper, we focus on anticipation - a capability…

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure.…

Emerging Technologies · Computer Science 2019-02-19 Olga Krestinskaya , Alex Pappachen James , Leon O. Chua

Memristors are low-power memory-holding resistors thought to be useful for neuromophic computing, which can compute via spike-interactions mediated through the device's short-term memory. Using interacting spikes, it is possible to build an…

Emerging Technologies · Computer Science 2018-01-09 Ella M. Gale

This paper presents a tutorial and review of SRAM-based Compute-in-Memory (CIM) circuits, with a focus on both Digital CIM (DCIM) and Analog CIM (ACIM) implementations. We explore the fundamental concepts, architectures, and operational…

Hardware Architecture · Computer Science 2024-11-25 Kentaro Yoshioka , Shimpei Ando , Satomi Miyagi , Yung-Chin Chen , Wenlun Zhang

We present a novel cryptography architecture based on memristor crossbar array, binary hypervectors, and neural network. Utilizing the stochastic and unclonable nature of memristor crossbar and error tolerance of binary hypervectors and…

Cryptography and Security · Computer Science 2022-01-28 Jack Cai , Amirali Amirsoleimani , Roman Genov

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

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…

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

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

Reservoir computing is a subfield of machine learning in which a complex system, or 'reservoir,' uses complex internal dynamics to non-linearly project an input into a higher-dimensional space. A single trainable output layer then inspects…

Emerging Technologies · Computer Science 2019-06-18 Wilkie Olin-Ammentorp , Karsten Beckmann , Nathaniel C. Cady

It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive…

Neural and Evolutionary Computing · Computer Science 2012-11-26 Farnood Merrikh-Bayat , Saeed Bagheri Shouraki , Iman Esmaili Paeen Afrakoti

As conventional memory technologies are challenged by their technological physical limits, emerging technologies driven by novel materials are becoming an attractive option for future memory architectures. Among these technologies,…

Materials Science · Physics 2015-05-28 Omid Kavehei , Said Al-Sarawi , Kyoung-Rok Cho , Kamran Eshraghian , Derek Abbott

Nanoscale resistive memories are expected to fuel dense integration of electronic synapses for large-scale neuromorphic system. To realize such a brain-inspired computing chip, a compact CMOS spiking neuron that performs in-situ learning…

Neural and Evolutionary Computing · Computer Science 2015-11-25 Xinyu Wu , Vishal Saxena , Kehan Zhu , Sakkarapani Balagopal

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

Memristor crossbar architecture is one of the most popular circuit configurations due to its wide range of practical applications. The crossbar architecture can emulate the weighted summation operation, called multiply and accumulate…

Emerging Technologies · Computer Science 2022-04-21 Alex James , Leon Chua

This paper proposes a new design for realizing grounded and floating meminductor emulators built with two operational transconductance amplifiers (OTAs) and two second-generation current conveyors. The proposed grounded and floating…

Signal Processing · Electrical Eng. & Systems 2024-01-15 Garima Shukla , Pratik Kumar , Sajal K. Paul

We present a comprehensive phenomenological model for the crossbar integrated metal-oxide continuous-state memristors. The model consists of static and dynamic equations, which are obtained by fitting a large amount of experimental data,…

Applied Physics · Physics 2018-11-27 H. Nili , A. Vincent , M. Prezioso , M. R. Mahmoodi , I. Kataeva , D. Strukov

With the increased attention to memristive-based in-memory analog computing (IMAC) architectures as an alternative for energy-hungry computer systems for machine learning applications, a tool that enables exploring their device- and…

Emerging Technologies · Computer Science 2023-06-14 Md Hasibul Amin , Mohammed E. Elbtity , Ramtin Zand
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