Results 21 to 30 of about 763 (210)
Fully analogue photonic reservoir computer [PDF]
AbstractIntroduced a decade ago, reservoir computing is an efficient approach for signal processing. State of the art capabilities have already been demonstrated with both computer simulations and physical implementations. If photonic reservoir computing appears to be promising a solution for ultrafast nontrivial computing, all the implementations ...
Duport, Francois +4 more
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Parallel and deep reservoir computing using semiconductor lasers with optical feedback
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 +2 more
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Bayesian Optimisation of Large-scale Photonic Reservoir Computers [PDF]
Introduction. Reservoir computing is a growing paradigm for simplified training of recurrent neural networks, with a high potential for hardware implementations. Numerous experiments in optics and electronics yield comparable performance to digital state-of-the-art algorithms.
Piotr Antonik +3 more
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Online spike-based recognition of digits with ultrafast microlaser neurons
Classification and recognition tasks performed on photonic hardware-based neural networks often require at least one offline computational step, such as in the increasingly popular reservoir computing paradigm.
Amir Masominia +3 more
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Scalable reservoir computing on coherent linear photonic processor
Optical computing holds promise for high-speed, low-energy information processing due to its large bandwidth and ability to multiplex signals. The authors propose a recurrent neural network implementation using reservoir computing architecture in an ...
Mitsumasa Nakajima +2 more
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Asynchronous photonic time-delay reservoir computing
Time-delay reservoir computing uses a nonlinear node associated with a feedback loop to construct a large number of virtual neurons in the neural network. The clock cycle of the computing network is usually synchronous with the delay time of the feedback loop, which substantially constrains the flexibility of hardware implementations.
Jia-Yan Tang +6 more
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Neuromorphic Computing Based on Silicon Photonics and Reservoir Computing [PDF]
We present our latest progress using new neuromorphic paradigms for optical information processing in silicon photonics. We show how passive reservoir computing chips can be used to perform a variety of tasks (bit level tasks, nonlinear dispersion compensation, etc.) at high speeds and low power consumption.
Andrew Katumba +7 more
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Photonic reservoir computer based on frequency multiplexing
Reservoir computing is a brain-inspired approach for information processing, well suited to analog implementations. We report a photonic implementation of a reservoir computer that exploits frequency domain multiplexing to encode neuron states. The system processes 25 comb lines simultaneously (i.e., 25 neurons), at a rate of 20 MHz.
Butschek, Lorenz +5 more
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Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction
Reservoir computing is a relatively recent computational paradigm that originates from a recurrent neural network and is known for its wide range of implementations using different physical technologies.
Mushegh Rafayelyan +4 more
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Hardware optimization for photonic time-delay reservoir computer dynamics
Reservoir computing (RC) is one kind of neuromorphic computing mainly applied to process sequential data such as time-dependent signals. In this paper, the bifurcation diagram of a photonic time-delay RC system is thoroughly studied, and a method of ...
Meng Zhang, Zhizhuo Liang, Z Rena Huang
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