Results 11 to 20 of about 2,079,335 (239)

Photonic reinforcement learning based on optoelectronic reservoir computing [PDF]

Scientific Reports, 2022
Reinforcement learning has been intensively investigated and developed in artificial intelligence in the absence of training data, such as autonomous driving vehicles, robot control, internet advertising, and elastic optical networks.
Kazutaka Kanno, Atsushi Uchida
doaj   +6 more sources

Photonic reservoir computing: a thematic review

JPhys Photonics
Reservoir computing offers a versatile approach to temporal information processing by exploiting the dynamics of nonlinear systems to enable learning with a linear readout.
Mohab Abdalla, Guy Van der Sande, Apostolos Argyris, Fabio Pavanello, Miguel C Soriano, Damien Rontani   +5 more
doaj   +7 more sources

Integrated photonic reservoir computing with an all-optical readout [PDF]

Optics Express, 2023
Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir computing over other neuromorphic paradigms is its straightforward readout system, which facilitates both rapid training and robust, fabrication variation-insensitive photonic ...
Chonghuai Ma, Joris Van Kerrebrouck, Hong Deng, Stijn Sackesyn, Emmanuel Gooskens, Bing Bai, Joni Dambre, Peter Bienstman   +7 more
core   +6 more sources

Microring Resonator-based Photonic Reservoir Computing [PDF]

2024 24th International Conference on Transparent Optical Networks (ICTON)
Reservoir computing is a recurrent computing architecture particularly suited for implementation on photonic hardware, especially in its time-delay (time-multiplexed) implementation. Here, we review our effort in timedelay reservoir computing based on a single nonlinear node consisting of a silicon microring resonator. We focus on relating the physical
Bernard J. Giron Castro, Christophe Peucheret, Francesco Da Ros   +2 more
core   +4 more sources

Hardware realization of neuromorphic computing with a 4–port photonic reservoir for modulation format identification

Neuromorphic Computing and Engineering
The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the performance of
Enes Şeker, Rijil Thomas, Guillermo von Hünefeld, Stephan Suckow, Mahdi Kaveh, Gregor Ronniger, Pooyan Safari, Isaac Sackey, David Stahl, Colja Schubert, Johannes Karl Fischer, Ronald Freund, Max C Lemme   +12 more
doaj   +2 more sources

Low-Loss Photonic Reservoir Computing with Multimode Photonic Integrated Circuits. [PDF]

Sci Rep, 2018
AbstractWe present a numerical study of a passive integrated photonics reservoir computing platform based on multimodal Y-junctions. We propose a novel design of this junction where the level of adiabaticity is carefully tailored to capture the radiation loss in higher-order modes, while at the same time providing additional mode mixing that increases ...
Katumba A, Heyvaert J, Schneider B, Uvin S, Dambre J, Bienstman P.   +5 more
europepmc   +5 more sources

Time-domain image processing using photonic reservoir computing [PDF]

EPJ Web of Conferences, 2023
Photonic computing has attracted much attention due to its great potential to accelerate artificial neural network operations. However, the processing of a large amount of data, such as image data, basically requires large-scale photonic circuits and is ...
Sunada Satoshi, Yamaguchi Tomoya
doaj   +1 more source

Multiphoton Quantum Reservoirs For Robust Multidimensional Computing. [PDF]

Adv Sci (Weinh)
Projective measurements reveal hidden multidimensional quantum networks within classical multiphoton fields, enabling robust quantum reservoirs for room‐temperature quantum simulation, prediction, and information processing. These networks transform noisy classical photonic platforms into scalable quantum computational architectures.
Hong M, Quiroz-Juarez MA, Dawkins RB, Mostafavi F, Ferdous J, Wilberg A, Rodriguez-Lara BM, Woodring J, You C, León-Montiel RJ, Magaña-Loaiza OS.   +10 more
europepmc   +2 more sources

Scalable wavelength-multiplexing photonic reservoir computing

APL Machine Learning, 2023
Photonic reservoir computing (PRC) is a special hardware recurrent neural network, which is featured with fast training speed and low training cost. This work shows a wavelength-multiplexing PRC architecture, taking advantage of the numerous longitudinal
Rui-Qian Li, Yi-Wei Shen, Bao-De Lin, Jingyi Yu, Xuming He, Cheng Wang   +5 more
doaj   +1 more source

Photonic reservoir computing approaches to nanoscale computation [PDF]

Proceedings of the Second Annual International Conference on Nanoscale Computing and Communication, 2015
This material is based on work in progress. Reservoir computing, originally a training technique for recurrent neural networks, exploits the computation that naturally occurs in physical dynamical systems. Reservoir computing with integrated nanophotonics potentially offers low-power, high-bandwidth signal processing for telecommunication applications.
Andrew Katumba, Peter Bienstman, Joni Dambre   +2 more
openaire   +3 more sources