Related papers: Memory circuit elements: from systems to applicati…
This paper gives an overview of recent progress in the brain inspired computing field with a focus on implementation using emerging memories as electronic synapses. Design considerations and challenges such as requirements and design…
An optical quantum memory can be broadly defined as a system capable of storing a useful quantum state through interaction with light at optical frequencies. During the last decade, intense research was devoted to their development, mostly…
In his seminal paper, Chua presented a fundamental physical claim by introducing the memristor, "The missing circuit element". The memristor equations were originally supposed to represent a passive circuit element because, with active…
In 1976, Leon Chua showed that a thermistor can be modeled as a memristive device. Starting from this statement we designed a circuit that has four circuit elements: a linear passive inductor, a linear passive capacitor, a nonlinear…
Memristors are non-volatile nano-resistors. Their resistance can be tuned by applied currents or voltages and set to a large number of levels between two limit values. Thanks to these properties, memristors are ideal building blocks for a…
Memory formation in matter is a theme of broad intellectual relevance; it sits at the interdisciplinary crossroads of physics, biology, chemistry, and computer science. Memory connotes the ability to encode, access, and erase signatures of…
Mobile devices, like sensor networks and MEMS actuators use mobile power supplies to ensure energy for their operation. These are mostly batteries. The lifetime of the devices depends on the power consumption and on the quality and…
Single-molecule magnets weakly coupled to two ferromagnetic leads act as memory devices in electronic circuits---their response depends on history, not just on the instantaneous applied voltage. We show that magnetic anisotropy introduces a…
The majority of microelectromechanical system (MEMS) devices must be combined with integrated circuits (ICs) for operation in larger electronic systems. While MEMS transducers sense or control physical, optical or chemical quantities, ICs…
In Phys. Rev. Lett. 91 167206 (2003), Sun et al. study memory effects in an interacting nanoparticle system with specific temperature and field protocols. The authors claim that the observed memory effects originate from spin-glass dynamics…
How humans and machines make sense of current inputs for relation reasoning and question-answering while putting the perceived information into context of our past memories, has been a challenging conundrum in cognitive science and…
Memristive systems and devices are potentially available for implementing reservoir computing (RC) systems applied to pattern recognition. However, the computational ability of memristive RC systems depends on intertwined factors such as…
This article surveys the landscape of semiconductor materials and devices research for the acceleration of machine learning (ML) algorithms. We observe a disconnect between the semiconductor and device physics and engineering communities,…
The transformer is a neural network component that can be used to learn useful representations of sequences or sets of data-points. The transformer has driven recent advances in natural language processing, computer vision, and…
Memory simulators are used to estimate application performance on advanced memory systems, yet they may exhibit significant discrepancies compared to real hardware. This paper investigates two key questions: (1) what causes these…
Recently memristor-based applications and circuits are receiving an increased attention. Furthermore, memristors are also applied in logic circuit design. Material implication logic is one of the main areas with memristors. In this paper an…
As the compute demands for machine learning and artificial intelligence applications continue to grow, neuromorphic hardware has been touted as a potential solution. New emerging devices like memristors, atomic switches, etc have shown…
In this article, we first point out a missing active-device while providing its theoretical definition and impact on electronics. This type of active devices has an inverse functionality of transistors, and is suggested to be called…
Memristor device modeling is currently a heavily researched topic and is becoming ever more important as memristor devices make their way into CMOS circuit designs, necessitating accurate and efficient memristor circuit simulations. In this…
There have been many attempts to implement neural networks in the analog circuit. Most of them had a lot of input terms, and most studies implemented neural networks in the analog circuit through a circuit simulation program called Spice to…