2018
DOI: 10.1063/1.5048199
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Rapid time series prediction with a hardware-based reservoir computer

Abstract: Reservoir computing is a neural network approach for processing time-dependent signals that has seen rapid development in recent years. Physical implementations of the technique using optical reservoirs have demonstrated remarkable accuracy and processing speed at benchmark tasks. However, these approaches require an electronic output layer to maintain high performance, which limits their use in tasks such as time-series prediction, where the output is fed back into the reservoir. We present here a reservoir c… Show more

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Cited by 88 publications
(67 citation statements)
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References 32 publications
(33 reference statements)
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“…(1), then perform prediction of the Lorenz system after that segment with Eq. (5). Because the Lorenz system is chaotic, forecasting must eventually fail.…”
Section: A Lorenz '63mentioning
confidence: 99%
“…(1), then perform prediction of the Lorenz system after that segment with Eq. (5). Because the Lorenz system is chaotic, forecasting must eventually fail.…”
Section: A Lorenz '63mentioning
confidence: 99%
“…A qualitative comparison between the original chaotic dynamics and its experimentally generated replica was done previously [8,9]. Here we go one step further and quantify the performance of our system for the long-term reconstruction of the dynamics.…”
Section: Resultsmentioning
confidence: 92%
“…Autonomous replication of chaotic systems has been demonstrated both experimentally [8,9] and by numerical simulations [10]. However, it has been observed that such autonomous reservoir computers can settle on a * miguel@ifisc.uib-csic.es dynamical behavior different from the one they have been trained for [9,10]. We go beyond previous approaches by demonstrating that noise added to the input data can result in better overall replication of the desired chaotic dynamics and enhance robustness against parameter variations.…”
Section: Introductionmentioning
confidence: 89%
See 1 more Smart Citation
“…Reservoir computing is a new approach to constructing recurrent neural networks. In particular, the echo state network (ESN) is a practical method for implementing a reservoir computer [1][2][3] and has been shown to be effective, for example, for chaotic time series prediction [4][5][6][7][8][9][10]. When applied to time series prediction, the ESN usually has three layers, i.e., the input layer consisting of a single node from which input data are generated, the reservoir layer consisting of sparsely coupled multiple nodes (reservoir network), and the output layer consisting of a single node from which predicted values are provided.…”
Section: Introductionmentioning
confidence: 99%