Results 21 to 30 of about 1,932,721 (285)
Reservoir Computing with Computational Matter
, 2018 The reservoir computing paradigm of information processing has emerged as a natural response to the problem of training recurrent neural networks. It has been realized that the training phase can be avoided provided a network has some well-defined properties, e.g. the echo state property. This idea has been generalized to arbitrary artificial dynamical
Zoran Konkoli +3 more
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Reservoir computing with swarms [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 We study swarms as dynamical systems for reservoir computing (RC). By example of a modified Reynolds boids model, the specific symmetries and dynamical properties of a swarm are explored with respect to a nonlinear time-series prediction task. Specifically, we seek to extract meaningful information about a predator-like driving signal from the swarm’s ...
Thomas Lymburn +3 more
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Reservoir computing with noise
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 This paper investigates in detail the effects of measurement noise on the performance of reservoir computing. We focus on an application in which reservoir computers are used to learn the relationship between different state variables of a chaotic system. We recognize that noise can affect the training and testing phases differently.
Chad Nathe +5 more
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Optoelectronic Reservoir Computing [PDF]
Scientific Reports, 2012 Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-
Paquot, Yvan +6 more
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Transport in reservoir computing
Physica D: Nonlinear Phenomena, 2023 Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system. These paradigms are used in information processing, machine learning, and computation. A fundamental question that needs to be addressed in this framework is the statistical relationship between the input and ...
G. Manjunath, Juan-Pablo Ortega
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Dimension of reservoir computers [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network. The nodes are all driven by a common driving signal. In this work, three dimension estimation methods, false nearest neighbor, covariance dimension, and Kaplan-Yorke dimension, are used to estimate the dimension of the reservoir dynamical system.
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Symmetry-aware reservoir computing [PDF]
Physical Review E, 2021 10 pages, 7 ...
Wendson A. S. Barbosa +7 more
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Optomechanical reservoir computing. [PDF]
Proc Natl Acad Sci U S ANonlinear dynamics are pervasive phenomena in natural and synthetic material systems, where time-varying signals from different physical stimuli in the environment influence the material system behavior. Physical reservoir computing leverages these nonlinear dynamics to produce complex input–output mappings by interpreting the dynamical system as a ...
Kiyabu S +8 more
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Proceedings of the 3rd ACM International Conference on Nanoscale Computing and Communication, 2016 Reservoir Computing (RC) is an umbrella term for adaptive computational paradigms that rely on an excitable dynamical system, also called the "reservoir." The paradigms have been shown to be particularly promising for temporal signal processing. RC was also explored as a potential candidate for emerging nanoscale architectures.
Goudarzi, Alireza, Teuscher, Christof
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Calibrated reservoir computers [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 We observe the presence of infinitely fine-scaled alternations within the performance landscape of reservoir computers aimed for chaotic data forecasting. We investigate the emergence of the observed structures by means of variations of the transversal stability of the synchronization manifold relating the observational and internal dynamical states ...
Y. A. Mabrouk, C. Räth
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