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Related papers: Towards Analog Memristive Controllers

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Recently, interest has grown for application of reconfigurable devices in robust and adaptive control systems. The main advantage of such devices is that its structure is not fixed and may be varied depending on the currently used control…

Instrumentation and Detectors · Physics 2007-05-23 V. F. Gubarev , L. M. Yakovleva , N. N. Aksenov , A. V. Palagin , V. N. Opanasenko , V. G. Sakharin

This article proposes a general approach to the simulation and design of a multilayer perceptron (MLP) network on the basis of cross-bar arrays of metal-oxide memristive devices. The proposed approach uses the ANNM theory, tolerance theory,…

Memristors have been at the forefront of nanoelectronics research for the last decade, offering a valuable component to reconfigurable computing. Their attributes have been studied extensively along with applications that leverage their…

Memristors, uniquely characterized by their pinched hysteresis loop fingerprints, have attracted significant research interest over the past decade, due to their enormous potential for novel computation and artificial intelligence…

Applied Physics · Physics 2025-08-07 Erion Uka , Chun Zhao

While most neuromorphic systems are based on nanoscale electronic devices, nature relies on ions for energy-efficient information processing. Therefore, finding memristive nanofluidic devices is a milestone toward realizing electrolytic…

Memristors are an emerging technology that enables artificial intelligence (AI) accelerators with high energy efficiency and radiation robustness -- properties that are vital for the deployment of AI on-board spacecraft. However, space…

Systems and Control · Electrical Eng. & Systems 2025-09-08 Zacharia A. Rudge , Dominik Dold , Moritz Fieback , Dario Izzo , Said Hamdioui

Neuromorphic computing has emerged as a promising avenue towards building the next generation of intelligent computing systems. It has been proposed that memristive devices, which exhibit history-dependent conductivity modulation, could…

Nanoscale metal oxide memristors have potential in the development of brain-inspired computing systems that are scalable and efficient1-3. In such systems, memristors represent the native electronic analogues of the biological synapses.…

Mesoscale and Nanoscale Physics · Physics 2016-12-21 Cheng-Chih Hsieh , Anupam Roy , Yao-Feng Chang , Davood Shahrjerdi , Sanjay K. Banerjee

CMOS technology and its continuous scaling have made electronics and computers accessible and affordable for almost everyone on the globe; in addition, they have enabled the solutions of a wide range of societal problems and applications.…

Emerging Technologies · Computer Science 2019-07-19 Jintao Yu , Hoang Anh Du Nguyen , Lei Xie , Mottaqiallah Taouil , Said Hamdioui

Memristors as emergent nano-electronic devices have been successfully fabricated and used in non-conventional and neuromorphic computing systems in the last years. Several behavioral or physical based models have been developed to explain…

Memristive systems are generalisations of memristors, which are resistors with memory. In this paper, we present a quantum description of memristive systems. Using this model we propose and experimentally demonstrate a simple and practical…

Mesoscale and Nanoscale Physics · Physics 2017-09-11 Ying Li , Gregory W. Holloway , Simon C. Benjamin , G. Andrew D. Briggs , Jonathan Baugh , Jan A. Mol

Memristive devices, whose resistance can be controlled by applying a voltage and further retained, are attractive as possible circuit elements for neuromorphic computing. This new type of devices poses a number of both technological and…

Mesoscale and Nanoscale Physics · Physics 2023-05-31 Oleg G. Kharlanov

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…

Mesoscale and Nanoscale Physics · Physics 2012-09-24 Carsten Timm , Massimiliano Di Ventra

Memristors have recently received significant attention as ubiquitous device-level components for building a novel generation of computing systems. These devices have many promising features, such as non-volatility, low power consumption,…

Emerging Technologies · Computer Science 2017-10-25 Sijia Liu , Yanzhi Wang , Makan Fardad , Pramod K. Varshney

Recent results in adaptive matter revived the interest in the implementation of novel devices able to perform brain-like operations. Here we introduce a training algorithm for a memristor network which is inspired in previous work on…

Emerging Technologies · Computer Science 2022-05-13 Juan Pablo Carbajal , Daniel Alejandro Martin , Dante Renato Chialvo

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

Brain-inspired computing aims to mimic cognitive functions like associative memory, the ability to recall complete patterns from partial cues. Memristor technology offers promising hardware for such neuromorphic systems due to its potential…

Machine Learning · Computer Science 2025-05-20 Chengping He , Mingrui Jiang , Keyi Shan , Szu-Hao Yang , Zefan Li , Shengbo Wang , Giacomo Pedretti , Jim Ignowski , Can Li

Since performance improvements of computers are stagnating, new technologies and computer paradigms are hot research topics. Memristor-based In-Memory Computing is one of the promising candidates for the post-CMOS era, which comes in many…

Emerging Technologies · Computer Science 2024-10-22 Fabian Seiler , Nima TaheriNejad

Brain inspired circuits can provide an alternative solution to implement computing architectures taking advantage of fault tolerance and generalisation ability of logic gates. In this brief, we advance over the memristive threshold circuit…

Emerging Technologies · Computer Science 2014-11-20 Alex Pappachen James , Dinesh S. Kumar , Arun Ajayan

Neuro-evolutionary methods have proven effective in addressing a wide range of tasks. However, the study of the robustness and generalizability of evolved artificial neural networks (ANNs) has remained limited. This has immense implications…

Neural and Evolutionary Computing · Computer Science 2024-07-22 Corinna Triebold , Anil Yaman
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