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Related papers: Active oscillatory associative memory

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According to mechanistic theories of working memory (WM), information is retained as persistent spiking activity of cortical neural networks. Yet, how this activity is related to changes in the oscillatory profile observed during WM tasks…

Neurons and Cognition · Quantitative Biology 2021-04-20 Nikita Novikov , Denis Zakharov , Victoria Moiseeva , Boris Gutkin

We study an excitable active rotator with slowly adapting nonlinear feedback and noise. Depending on the adaptation and the noise level, this system may display noise-induced spiking, noise-perturbed oscillations, or stochastic busting. We…

Adaptation and Self-Organizing Systems · Physics 2020-08-26 Igor Franović , Serhiy Yanchuk , Sebastian Eydam , Iva Bačić , Matthias Wolfrum

We study the dynamics of coupled oscillator networks with higher-order interactions and their ability to store information. In particular, the fixed points of these oscillator systems consist of two clusters of oscillators that become…

Adaptation and Self-Organizing Systems · Physics 2021-08-03 Per Sebastian Skardal , Alex Arenas

Inspired by the observation of a distributed time delay in the nonlinear response of an optical resonator, we investigate the effects of a similar delay on a noise-driven mechanical oscillator. For a delay time that is commensurate with the…

Optics · Physics 2022-02-16 K. J. H. Peters , S. R. K. Rodriguez

Fluctuations play a central role in many fields of physics, from quantum electrodynamics to statistical mechanics. In active matter physics, most models focus on thermal fluctuations due to a surrounding solvent. An alternative but much…

Soft Condensed Matter · Physics 2025-04-17 Sebastian Fehlinger , Kai Cui , Arooj Sajjad , Heinz Koeppl , Benno Liebchen

An efficient technique is introduced for model inference of complex nonlinear dynamical systems driven by noise. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is…

Data Analysis, Statistics and Probability · Physics 2007-05-23 V. N. Smelyanskiy , D. A. Timucin , A. Bandrivskyy , D. G. Luchinsky

We study an information engine operating in an active bath, where a Brownian particle confined in a harmonic trap undergoes feedback-driven displacement cycles. Unlike thermal environments, active baths exhibit temporally correlated…

Statistical Mechanics · Physics 2025-11-27 Sehoon Bahng , Jae Sung Lee , Cheol-Min Ghim

Evolution equations are derived for the amplitudes of associative memories: heterogeneous states stored in the connectivity of distributed systems with non-local interactions. The resulting coupled amplitude equations describe the…

Neurons and Cognition · Quantitative Biology 2025-10-20 Akke Mats Houben

Continuous attractors have been used to understand recent neuroscience experiments where persistent activity patterns encode internal representations of external attributes like head direction or spatial location. However, the conditions…

Disordered Systems and Neural Networks · Physics 2019-01-01 Weishun Zhong , Zhiyue Lu , David J Schwab , Arvind Murugan

We propose a network of oscillators to retrieve given patterns in which the oscillators keep a fixed phase relationship with one another. In this description, the phase and the amplitude of the oscillators can be regarded as the timing and…

adap-org · Physics 2009-10-22 Toshio Aoyagi

Active systems, which are driven out of equilibrium by local non-conservative forces, can adopt unique behaviors and configurations. An important challenge in the design of novel materials which utilize such properties is to precisely…

Soft Condensed Matter · Physics 2022-08-09 Gregory Rassolov , Laura Tociu , Étienne Fodor , Suriyanarayanan Vaikuntanathan

Using the Hopfield model as a benchmark case, the present work focuses on the investigation of partially annealed associative neural networks, wherein neural dynamics is coupled to slowly evolving patterns within the…

Disordered Systems and Neural Networks · Physics 2026-05-12 Linda Albanese , Andrea Alessandrelli , Adriano Barra , Silvio Franz , Federico Ricci-Tersenghi

The test bench time needed for model-based calibration can be reduced with active learning methods for test design. This paper presents an improved strategy for active output selection. This is the task of learning multiple models in the…

Machine Learning · Computer Science 2021-01-12 Adrian Prochaska , Julien Pillas , Bernard Bäker

An associative memory is a framework of content-addressable memory that stores a collection of message vectors (or a dataset) over a neural network while enabling a neurally feasible mechanism to recover any message in the dataset from its…

Machine Learning · Statistics 2016-11-30 Arya Mazumdar , Ankit Singh Rawat

We propose a dynamical approach to quantum memories using an oscillator-cavity model. This overcomes the known difficulties of achieving high quantum input-output fidelity with storage times long compared to the input signal duration. We…

Quantum Physics · Physics 2013-05-29 Q. Y. He , M. D. Reid , E. Giacobino , J. Cviklinski , P. D Drummond

A noise source model, consisting of a pulse sequence at random times with memory, is presented. By varying the memory we can obtain variable randomness of the stochastic process. The delay time between pulses, i. e. the noise memory,…

Statistical Mechanics · Physics 2009-09-29 O. Chichigina , D. Valenti , B. Spagnolo

Networks of phase oscillators can serve as dense associative memories if they incorporate higher-order coupling beyond the classical Kuramoto model's pairwise interactions. Here we introduce a generalized Kuramoto model with combined…

Adaptation and Self-Organizing Systems · Physics 2025-07-30 Jona Nagerl , Natalia G. Berloff

This paper deals with the phase noise affecting communication systems, where local oscillators are employed to obtain reference signals for carrier and timing synchronizations. The most common discrete-time phase noise channel model is…

Information Theory · Computer Science 2024-06-21 Amina Piemontese , Giulio Colavolpe , Thomas Eriksson

We find that sensory noise delivered together with a weak periodic signal not only enhances nonlinear response of neuronal networks, but also improves the synchronization of the response to the signal. We reveal this phenomenon in neuronal…

Neurons and Cognition · Quantitative Biology 2015-08-25 M. A. Lopes , K. -E. Lee , A. V. Goltsev , J. F. F. Mendes

Active learning shows promise to decrease test bench time for model-based drivability calibration. This paper presents a new strategy for active output selection, which suits the needs of calibration tasks. The strategy is actively learning…

Machine Learning · Computer Science 2021-02-24 Adrian Prochaska , Julien Pillas , Bernard Bäker
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