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Related papers: Memristor Circuits for Simulating Nonlinear Dynami…

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We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key idea is to develop a new control-theoretic regularizer for dynamics fitting rooted in the notion of…

Systems and Control · Computer Science 2018-11-13 Sumeet Singh , Vikas Sindhwani , Jean-Jacques E. Slotine , Marco Pavone

In this paper we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state transitioning devices, which switch between two discrete states…

Emerging Technologies · Computer Science 2016-08-22 Abhinav Parihar , Nikhil Shukla , Matthew Jerry , Suman Datta , Arijit Raychowdhury

Many complex systems can spontaneously oscillate under non-periodic forcing. Such self-oscillators are commonplace in biological and technological assemblies where temporal periodicity is needed, such as the beating of a human heart or the…

Digital circuits based on residue number systems have been considered to produce a pseudo-random behavior. The present work is an initial step towards the complete implementation of those systems for similar applications using quantum…

Quantum Physics · Physics 2025-06-03 Andrea Ceschini , Antonello Rosato , Massimo Panella

It has been observed through experiments and SPICE simulations that logical circuits based upon Chua's circuit exhibit complex dynamical behavior. This behavior can be used to design analogs of more complex logic families and some…

Chaotic Dynamics · Physics 2018-03-26 Aminur Rahman , Ian Jordan , Denis Blackmore

Limit cycles are self-sustained, closed trajectories in phase space representing (un)-stable, periodic behavior in nonlinear dynamical systems. They underpin diverse natural phenomena, from neuronal firing patterns to engineering…

Adaptation and Self-Organizing Systems · Physics 2025-08-15 Sandip Saha , Suvam Pal , Dibakar Ghosh

Memristive associative learning has gained significant attention for its ability to mimic fundamental biological learning mechanisms while maintaining system simplicity. In this work, we introduce a high-order memristive associative…

Neural and Evolutionary Computing · Computer Science 2024-10-23 Shengbo Wang , Xuemeng Li , Jialin Ding , Weihao Ma , Ying Wang , Luigi Occhipinti , Arokia Nathan , Shuo Gao

In the pursuit of scalable and energy-efficient neuromorphic devices, recent research has unveiled a novel category of spiking oscillators, termed "thermal neuristors." These devices function via thermal interactions among neighboring…

Disordered Systems and Neural Networks · Physics 2024-07-12 Yuan-Hang Zhang , Chesson Sipling , Erbin Qiu , Ivan K. Schuller , Massimiliano Di Ventra

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

Non-linear dynamics is not a usually covered topic in undergraduate physics courses. However, its importance within classical mechanics and the general theory of dynamical systems is unquestionable. In this work we show that this subject…

Classical Physics · Physics 2024-08-09 Ronaldo S. S. Vieira , Luiz H. R. Daniel , Marcus A. M. de Aguiar

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…

Mesoscale and Nanoscale Physics · Physics 2016-05-26 Steven Lequeux , Joao Sampaio , Vincent Cros , Kay Yakushiji , Akio Fukushima , Rie Matsumoto , Hitoshi Kubota , Shinji Yuasa , Julie Grollier

Self-sustained oscillators are ubiquitous and essential for metrology, communications, time reference, and geolocation. In its most basic form an oscillator consists of a resonator driven on-resonance, through feedback, to create a periodic…

Mesoscale and Nanoscale Physics · Physics 2013-05-21 L. G. Villanueva , E. Kenig , R. B. Karabalin , M. H. Matheny , R. Lifshitz , M. C. Cross , M. L. Roukes

Many physical, chemical and biological systems can be modeled by means of random-frequency harmonic oscillator systems. Even though the noise-free evolution of harmonic oscillator systems can be easily implemented, the way to experimentally…

Classical Physics · Physics 2014-07-11 R. de J. León-Montiel , J. Svozilík , Juan P. Torres

Memory effects are ubiquitous in nature and are particularly relevant at the nanoscale where the dynamical properties of electrons and ions strongly depend on the history of the system, at least within certain time scales. We review here…

Mesoscale and Nanoscale Physics · Physics 2011-03-02 Yuriy V. Pershin , Massimiliano Di Ventra

Process variations are a major concern in today's chip design since they can significantly degrade chip performance. To predict such degradation, existing circuit and MEMS simulators rely on Monte Carlo algorithms, which are typically too…

Computational Engineering, Finance, and Science · Computer Science 2016-11-18 Zheng Zhang , Xiu Yang , Giovanni Marucci , Paolo Maffezzoni , Ibrahim , M. Elfadel , George Em Karniadakis , Luca Daniel

The coupled electron-nuclear spin system in an InGaAs semiconductor as testbed of nonlinear dynamics can develop auto-oscillations, resembling time-crystalline behavior, when continuously excited by a circularly polarized laser. We expose…

Mesoscale and Nanoscale Physics · Physics 2025-03-28 Alex Greilich , Nataliia E. Kopteva , Vladimir L. Korenev , Manfred Bayer

Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tuneable conductivity properties enable the imitation of synaptic behaviour. Multipore nanofluidic memristors have shown their…

Applied Physics · Physics 2024-09-17 Agustin Bou , Patricio Ramirez , Juan Bisquert

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph…

Disordered Systems and Neural Networks · Physics 2017-03-08 Francesco Caravelli , Fabio Lorenzo Traversa , Massimiliano Di Ventra

In this paper, based on the classic Chua's circuit, a charge-controlled memristor is introduced to design a novel four-dimensional chaotic system. The complex dynamics of the novel chaotic system such as equilibrium points, stability,…

Chaotic Dynamics · Physics 2020-09-03 S. H. Yan , Z. L. Song , W. L. Shi , W. L. Zhao

In this paper, we introduce some interesting features of a memristor CNN (Cellular Neural Network). We first show that there is the similarity between the dynamics of memristors and neurons. That is, some kind of flux-controlled memristors…

Neural and Evolutionary Computing · Computer Science 2019-02-15 Makoto Itoh