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Principled neuromorphic reservoir computing [PDF]
Nature CommunicationsReservoir computing advances the intriguing idea that a nonlinear recurrent neural circuit—the reservoir—can encode spatio-temporal input signals to enable efficient ways to perform tasks like classification or regression. However, recently the idea of a
Denis Kleyko +5 more
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AI, 2022 Noise of any kind can be an issue when translating results from simulations to the real world. We suddenly have to deal with building tolerances, faulty sensors, or just noisy sensor readings.
Christoph Walter Senn, Itsuo Kumazawa
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Potential implementation of reservoir computing models based on magnetic skyrmions
AIP Advances, 2018 Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality.
George Bourianoff +3 more
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Harvested reservoir computing from road traffic dynamics [PDF]
Scientific ReportsReservoir computing (RC) has gained attention as an efficient machine learning method for time series prediction because of its low computational costs and simple learning process.
Ryunosuke Fukuzaki +2 more
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Gate insulator stack engineering for fully CMOS-compatible reservoir computing [PDF]
Nano ConvergenceThe need for processing complex and temporal datasets has increased with the rise of artificial intelligence. In this context, reservoir computing, which utilizes the short-term memory of the reservoir to map input data into a high-dimensional space, has
Joon Hwang +4 more
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Reservoir computing with generalized readout based on generalized synchronization [PDF]
Scientific ReportsReservoir computing is a machine learning framework that exploits nonlinear dynamics, exhibiting significant computational capabilities. One of the defining characteristics of reservoir computing is that only linear output, given by a linear combination ...
Akane Ohkubo, Masanobu Inubushi
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Deterministic reservoir computing for chaotic time series prediction [PDF]
Scientific ReportsReservoir Computing was shown in recent years to be useful as efficient to learn networks in the field of time series tasks. Their randomized initialization, a computational benefit, results in drawbacks in theoretical analysis of large random graphs ...
Johannes Viehweg +2 more
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Parallel and deep reservoir computing using semiconductor lasers with optical feedback
Nanophotonics, 2022 Photonic reservoir computing has been intensively investigated to solve machine learning tasks effectively. A simple learning procedure of output weights is used for reservoir computing.
Hasegawa Hiroshi +2 more
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Reservoir concatenation and the spectrum distribution of concatenated reservoir state matrices
AIP Advances, 2023 Reservoir computing, one of the state-of-the-art machine learning architectures, processes time-series data generated by dynamical systems. Nevertheless, we have realized that reservoir computing with the conventional single-reservoir structure suffers ...
Jaesung Choi +3 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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