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Zuowei Ye, Guidong Zhang
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Long short-term memory
10.1007/978-3-642-24797-2_4 · 2012
Deep learning
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Predicting nonlinear dynamics of optical solitons in optical fiber via the SCPINN
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The “echo state” approach to analysing and training recurrent neural networks-with an erratum note
2001
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10.1016/j.cosrev.2009.03.005 · 2009
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2012
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Deterministic nonperiodic flow
10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2 · 1963
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An equation for continuous chaos
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Oscillation and chaos in physiological control systems
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Circuit realization, bifurcations, chaos and hyperchaos in a new 4D system
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Circuit realization, bifurcations, chaos and hyperchaos in a new 4D system
10.1016/j.amc.2014.04.109 · doi-reference
Oscillation and chaos in physiological control systems
10.1126/science.267326 · doi-reference
An equation for continuous chaos
10.1016/0375-9601(76)90101-8 · doi-reference
Minimal design of multi-stage reservoir based on small-world network
10.1088/2631-8695/ada480 · doi-reference
Computational efficiency of multi-step learning echo state networks for nonlinear time series prediction
10.1109/access.2022.3158755 · doi-reference
Constructing polynomial libraries for reservoir computing in nonlinear dynamical system forecasting
10.1103/physreve.109.024227 · doi-reference
Data-driven predictions of a multiscale Lorenz 96 chaotic system using machine-learning methods: reservoir computing, artificial neural network, and long short-term memory network
10.5194/npg-27-373-2020 · doi-reference
Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics
10.1016/j.neunet.2020.02.016 · doi-reference
Attention-enhanced reservoir computing
10.1103/physrevapplied.22.014039 · doi-reference
Persistence of chaos in coupled Lorenz systems
10.1016/j.chaos.2016.12.017 · doi-reference
Deterministic nonperiodic flow
10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2 · doi-reference
Input driven optimization of echo state network parameters for prediction on chaotic time series
10.1038/s41598-025-18261-x · doi-reference
Principled neuromorphic reservoir computing
10.1038/s41467-025-55832-y · doi-reference
Delay-embedded reservoir computing with single memristor for scale-efficient temporal signal processing
10.1016/j.chaos.2025.117842 · doi-reference
Hybrid residual reservoir computing using dynamic memristor for time series prediction
10.1016/j.chaos.2026.117866 · doi-reference
Security-enhanced coherent optical chaotic secure communication based on linearly coupled reservoir computing
10.1016/j.chaos.2025.117548 · doi-reference
The optoelectronic reservoir computing system based on parallel multi-time-delay feedback loops for time-series prediction and optical performance monitoring
10.1016/j.chaos.2024.115306 · doi-reference
Synchronization of spatiotemporal chaos and reservoir computing via scalar signals
10.1016/j.chaos.2023.113314 · doi-reference
Reservoir computing approaches to recurrent neural network training
10.1016/j.cosrev.2009.03.005 · doi-reference
Predicting nonlinear dynamics of optical solitons in optical fiber via the SCPINN
10.1016/j.chaos.2022.112908 · doi-reference
Deep learning
10.1038/nature14539 · doi-reference
Long short-term memory
10.1007/978-3-642-24797-2_4 · doi-reference
Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography
10.1103/physreve.98.012215 · doi-reference
Symmetry enhanced prediction of spatio-temporal chaotic system with reservoir computing
10.1016/j.chaos.2025.117634 · doi-reference
Model-free prediction of large spatiotemporally chaotic systems from data: a reservoir computing approach
10.1103/physrevlett.120.024102 · doi-reference
Forecasting of noisy chaotic systems with deep neural networks
10.1016/j.chaos.2021.111570 · doi-reference
Chaotic time series prediction of nonlinear systems based on various neural network models
10.1016/j.chaos.2023.113971 · doi-reference