Results 21 to 30 of about 19,366 (302)
Brain connectivity meets reservoir computing [PDF]
PLOS Computational Biology, 2021 The connectivity of Artificial Neural Networks (ANNs) is different from the one observed in Biological Neural Networks (BNNs). Can the wiring of actual brains help improve ANNs architectures? Can we learn from ANNs about what network features support computation in the brain when solving a task?
Fabrizio Damicelli +2 more
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Scientific Reports, 2023 Reservoir computing is a brain heuristic computing paradigm that can complete training at a high speed. The learning performance of a reservoir computing system relies on its nonlinearity and short-term memory ability.
Zhiqiang Liao +5 more
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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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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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Quantum reservoir computing with a single nonlinear oscillator
Physical Review Research, 2021 Realizing the promise of quantum information processing remains a daunting task given the omnipresence of noise and error. Adapting noise-resilient classical computing modalities to quantum mechanics may be a viable path towards near-term applications in
L. C. G. Govia +4 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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Hybrid quantum-classical reservoir computing of thermal convection flow
Physical Review Research, 2022 We simulate the nonlinear chaotic dynamics of Lorenz-type models for a classical two-dimensional thermal convection flow with three and eight degrees of freedom by a hybrid quantum-classical reservoir computing model.
Philipp Pfeffer +2 more
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Leveraging plant physiological dynamics using physical reservoir computing
Scientific Reports, 2022 Plants are complex organisms subject to variable environmental conditions, which influence their physiology and phenotype dynamically. We propose to interpret plants as reservoirs in physical reservoir computing. The physical reservoir computing paradigm
Olivier Pieters +3 more
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Synchronizing chaos using reservoir computing
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 We attempt to achieve complete synchronization between a drive system unidirectionally coupled with a response system, under the assumption that limited knowledge on the states of the drive is available at the response. Machine-learning techniques have been previously implemented to estimate the states of a dynamical system from limited measurements ...
Amirhossein Nazerian +3 more
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Optimizing memory in reservoir computers [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 A reservoir computer is a way of using a high dimensional dynamical system for computation. One way to construct a reservoir computer is by connecting a set of nonlinear nodes into a network. Because the network creates feedback between nodes, the reservoir computer has memory.
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