Results 1 to 10 of about 101,043 (267)

Leveraging plant physiological dynamics using physical reservoir computing. [PDF]

Sci Rep, 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
Pieters O, De Swaef T, Stock M, Wyffels F.   +3 more
europepmc   +5 more sources

Harnessing synthetic active particles for physical reservoir computing. [PDF]

Nat Commun, 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 ...
Wang X, Cichos F.
europepmc   +5 more sources

Photonic Physical Reservoir Computing with Tunable Relaxation Time Constant. [PDF]

Adv Sci (Weinh), 2023
Recent years have witnessed a rising demand for edge computing, and there is a need for methods to decrease the computational cost while maintaining a high learning performance when processing information at arbitrary edges.
Yamazaki Y, Kinoshita K.
europepmc   +4 more sources

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

Sci Rep, 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.
Bhovad P, Li S.
europepmc   +2 more sources

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, Daniele Pinna, Matthias Sitte, Karin Everschor-Sitte   +3 more
doaj   +3 more sources

Interface-type tunable oxygen ion dynamics for physical reservoir computing. [PDF]

Nat Commun, 2023
Reservoir computing can more efficiently be used to solve time-dependent tasks than conventional feedforward network owing to various advantages, such as easy training and low hardware overhead.
Liu Z, Zhang Q, Xie D, Zhang M, Li X, Zhong H, Li G, He M, Shang D, Wang C, Gu L, Yang G, Jin K, Ge C.   +13 more
europepmc   +2 more sources

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

Nat Commun
The scaling law of deep learning, which governs the relationship between model size and performance, has led to critical concerns regarding efficiency and sustainability.
Han X, Qi Z, Kundrat V, Li H, Li Z, Guo X, Mao P, Zheng W, Hou S, Liu R, Wu H, Wang P, Zak A, Liu W, Tenne R, Guo Y.   +15 more
europepmc   +2 more sources

Fiber Memristor-Based Physical Reservoir Computing for Multimodal Sleep Monitoring. [PDF]

Research (Wash D C)
Real-time wearable sleep monitors process diverse biological signals while operating under tight energy and computation budgets. The existing algorithms are facing problems of high energy consumption due to separate hardware storage and computation units.
Zhang J, Zhu Z, Meng J, Wang T.
europepmc   +2 more sources

Harvested reservoir computing from road traffic dynamics. [PDF]

Sci Rep
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.
Fukuzaki R, Noguchi T, Ando H.
europepmc   +2 more sources

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

Adv Sci (Weinh)
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.
Wang J, Li S.
europepmc   +2 more sources