Results 1 to 10 of about 7,314,717 (264)

Harnessing synthetic active particles for physical reservoir computing [PDF]

Nature Communications, 2023
The processing of information is an indispensable property of living systems realized by networks of active processes with enormous complexity. They have inspired many variants of modern machine learning, one of them being reservoir computing, in which ...
Xiangzun Wang, Frank Cichos
doaj   +6 more sources

Leveraging plant physiological dynamics using physical reservoir computing [PDF]

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, Tom De Swaef, Michiel Stock, Francis wyffels   +3 more
doaj   +3 more sources

Memristive Physical Reservoir Computing [PDF]

Advanced Science
Reservoir computing (RC) has emerged as an efficient neuromorphic framework for temporal information processing, offering low training complexity and hardware‐friendly implementation. Memristors’ nonlinear dynamics and input‐dependent memory effects make
Dian Jiao, Ziyuan Wang, Jingrui Wang, Li Zhang, Xianhua Wei, Lingxiang Hu, Zongxiao Li, Athanasios V. Vasilakos, Zhizhen Ye, Fei Zhuge   +9 more
doaj   +3 more sources

Physical reservoir computing with origami and its application to robotic crawling [PDF]

Scientific Reports, 2021
A new paradigm called physical reservoir computing has recently emerged, where the nonlinear dynamics of high-dimensional and fixed physical systems are harnessed as a computational resource to achieve complex tasks.
Priyanka Bhovad, Suyi Li
doaj   +6 more sources

Physical Implementation of Reservoir Computing through Electrochemical Reaction [PDF]

Advanced Science, 2022
Nonlinear dynamical systems serving reservoir computing enrich the physical implementation of computing systems. A method for building physical reservoirs from electrochemical reactions is provided, and the potential of chemical dynamics as computing ...
Shaohua Kan, Kohei Nakajima, Tetsuya Asai, Megumi Akai‐Kasaya   +3 more
doaj   +4 more sources

Morphologically tunable mycelium chips for physical reservoir computing [PDF]

Scientific Reports
We introduce a neuromorphic computing substrate based on PEDOT:PSS-infused mycelium, a biofabricated, morphologically tunable material that can be engineered into electrically active components including resistors, capacitors, and non-linear elements ...
Orkan Telhan, Jake Winiski, Damen Schaak, Michael Siegel, Neale Petrillo, Eben Bayer   +5 more
doaj   +3 more sources

Experimental Demonstration of High‐Performance Physical Reservoir Computing with Nonlinear Interfered Spin Wave Multidetection

Advanced Intelligent Systems, 2023
Physical reservoir computing, which is a promising method for the implementation of highly efficient artificial intelligence devices, requires a physical system with nonlinearity, fading memory, and the ability to map in high dimensions.
Wataru Namiki, Daiki Nishioka, Yu Yamaguchi, Takashi Tsuchiya, Tohru Higuchi, Kazuya Terabe   +5 more
doaj   +2 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
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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
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A physical reservoir involving frequency virtual nodes for structural damage detection [PDF]

Scientific Reports
This study proposes a physical reservoir computing approach for structural damage detection, in which the target structure itself serves as the physical reservoir.
Konosuke Takashima, Naoko Watanabe, Motoaki Hiraga, Nanako Miura, Arata Masuda   +4 more
doaj   +2 more sources