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Principled neuromorphic reservoir computing [PDF]

Nature Communications
Reservoir 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, Christopher J. Kymn, Anthony Thomas, Bruno A. Olshausen, Friedrich T. Sommer, E. Paxon Frady   +5 more
doaj   +5 more sources

Abstract Reservoir Computing

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
doaj   +2 more sources

Harvested reservoir computing from road traffic dynamics [PDF]

Scientific Reports
Reservoir 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, Takahiro Noguchi, Hiroyasu Ando   +2 more
doaj   +2 more sources

Gate insulator stack engineering for fully CMOS-compatible reservoir computing [PDF]

Nano Convergence
The 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, Min-Kyu Park, Jeonghyun Kim, Jong-Ho Bae, Jong-Ho Lee   +4 more
doaj   +2 more sources

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction [PDF]

Nature Communications
Reservoir computing has attracted considerable attention due to its low training cost. However, existing neuromorphic hardware, focusing mainly on shallow-reservoir computing, faces challenges in providing adequate spatial and temporal scales ...
Changsong Gao, Di Liu, Chenhui Xu, Weidong Xie, Xianghong Zhang, Junhua Bai, Zhixian Lin, Cheng Zhang, Yuanyuan Hu, Tailiang Guo, Huipeng Chen   +10 more
doaj   +2 more sources

Reservoir computing with generalized readout based on generalized synchronization [PDF]

Scientific Reports
Reservoir 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
doaj   +2 more sources

Deterministic reservoir computing for chaotic time series prediction [PDF]

Scientific Reports
Reservoir 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, Constanze Poll, Patrick Mäder   +2 more
doaj   +2 more sources

Neuromorphic Reservoir Computing with Memristive Nanofluidic Diodes. [PDF]

Nano Lett
Portillo S, Ramirez P, Mafe S, Cervera J.   +3 more
europepmc   +2 more sources

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, Kanno Kazutaka, Uchida Atsushi   +2 more
doaj   +1 more source

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, Eonyoung Park, Bongsoo Jang, Yunho Kim   +3 more
doaj   +1 more source