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Recent advances in physical reservoir computing: A review

Neural Networks, 2019
Reservoir computing is a computational framework suited for temporal/sequential data processing. It is derived from several recurrent neural network models, including echo state networks and liquid state machines. A reservoir computing system consists of a reservoir for mapping inputs into a high-dimensional space and a readout for pattern analysis ...
Naoki Kanazawa, Gouhei Tanaka, Akira Hirose   +2 more
exaly   +4 more sources

Physical reservoir computing: a tutorial

Natural Computing
AbstractThis tutorial covers physical reservoir computing from a computer science perspective. It first defines what it means for a physical system to compute, rather than merely evolve under the laws of physics. It describes the underlying computational model, the Echo State Network (ESN), and also some variants designed to make physical ...
Susan Stepney, Stepney Susan
exaly   +3 more sources

Very-large-scale mimetic optogenetic synapses for physical reservoir computing [PDF]

Nature Communications
The scaling law of deep learning, which governs the relationship between model size and performance, has led to critical concerns regarding efficiency and sustainability.
Xinyi Han, Zhiying Qi, Vojtech Kundrat, Huanjing Li, Zhonggui Li, Xiaoyu Guo, Pengcheng Mao, Weiguo Zheng, Shuai Hou, Ruibin Liu, Hanchun Wu, Panding Wang, Alla Zak, Weifan Liu, Reshef Tenne, Yao Guo   +15 more
doaj   +2 more sources

Analogue and Physical Reservoir Computing Using Water Waves: Applications in Power Engineering and Beyond

Energies, 2023
More than 3.5 billion people live in rural areas, where water and water energy resources play an important role in ensuring sustainable and productive rural economies.
Ivan S. Maksymov
doaj   +3 more sources

Implementation of reservoir computing using coupled microelectromechanical drum resonators via sideband-pumped phonon–cavity dynamics [PDF]

Microsystems & Nanoengineering
Reservoir computing is a bio-inspired machine learning paradigm that exploits the intrinsic dynamics of nonlinear systems with fading memory for efficient temporal information processing.
Theresa Farah, Loïc Flis, Pierre Laly, Guo-En Chang, Jun-Yu Ou, Yoshishige Tsuchiya, Yan Pennec, Bahram Djafari-Rouhani, Xin Zhou   +8 more
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

Re‐Purposing a Modular Origami Manipulator Into an Adaptive Physical Computer for Machine Learning and Robotic Perception [PDF]

Advanced Science
Physical computing has emerged as a powerful tool for performing intelligent tasks directly in the mechanical domain of functional materials and robots, reducing our reliance on the more traditional CMOS computers.
Jun Wang, Suyi Li
doaj   +2 more sources

Embodying physical computing into soft robots [PDF]

Nature Communications
Softening and onboarding computers and controllers is one of the final frontiers in soft robotics towards their robustness and intelligence for everyday use. In this regard, embodying soft and physical computing presents exciting potential.
Jun Wang, Ziyang Zhou, Ardalan Kahak, Suyi Li   +3 more
doaj   +2 more sources

Physics-based approach to developing physical reservoir computers

Physical Review Research
Reservoir computing leverages the dynamic properties of a fixed, randomly connected neural network to facilitate simplified training and enhanced computational efficiency. Many forms of physical reservoir computers have been proposed.
Vahideh Shirmohammadli, Behraad Bahreyni
doaj   +2 more sources

Spatial analysis of physical reservoir computers

Physical Review Applied, 2023
7 Pages, 5 ...
Jake Love, Robin Msiska, Jeroen Mulkers, George Bourianoff, Jonathan Leliaert, Karin Everschor-Sitte   +5 more
openaire   +3 more sources