Approximate GP Inference for Nonlinear Dynamical System Identification Using Data-Driven Basis Set

IEEE Access ◽

10.1109/access.2020.2994089 ◽

2020 ◽

Vol 8 ◽

pp. 90665-90675

Author(s):

Hina Shoukat ◽

Muhammad Tahir ◽

Khurram Ali

Keyword(s):

Dynamical System ◽

System Identification ◽

Nonlinear Dynamical System ◽

Basis Set ◽

Data Driven ◽

Nonlinear Dynamical ◽

Dynamical System Identification ◽

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An Improved Approach to Nonlinear Dynamical System Identification using PID Neural Networks

International Journal of Nonlinear Sciences and Numerical Simulation ◽

10.1515/ijnsns.2006.7.2.177 ◽

2006 ◽

Vol 7 (2) ◽

Author(s):

Shou-Ju Li ◽

Ying-Xi Liu

Keyword(s):

Dynamical System ◽

Neural Networks ◽

System Identification ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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Nonlinear dynamical system identification using unscented Kalman filter

10.1063/1.4968052 ◽

2016 ◽

Author(s):

M. Javvad ur Rehman ◽

Sarat Chandra Dass ◽

Vijanth Sagayan Asirvadam

Keyword(s):

Dynamical System ◽

Kalman Filter ◽

System Identification ◽

Unscented Kalman Filter ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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Open-loop training of recurrent neural networks for nonlinear dynamical system identification

IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222) ◽

10.1109/ijcnn.2001.939534 ◽

2002 ◽

Author(s):

D. Liu

Keyword(s):

Dynamical System ◽

Neural Networks ◽

System Identification ◽

Recurrent Neural Networks ◽

Nonlinear Dynamical System ◽

Open Loop ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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A Kushner–Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification

Physica D Nonlinear Phenomena ◽

10.1016/j.physd.2013.12.007 ◽

2014 ◽

Vol 270 ◽

pp. 46-59 ◽

Author(s):

S. Sarkar ◽

S.R. Chowdhury ◽

M. Venugopal ◽

R.M. Vasu ◽

D. Roy

Keyword(s):

Dynamical System ◽

Monte Carlo ◽

System Identification ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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Nonlinear dynamical system identification with dynamic noise and observational noise

Physica D Nonlinear Phenomena ◽

10.1016/j.physd.2006.08.013 ◽

2006 ◽

Vol 223 (1) ◽

pp. 54-68 ◽

Author(s):

Tomomichi Nakamura ◽

Michael Small

Keyword(s):

Dynamical System ◽

System Identification ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Dynamic Noise ◽

Observational Noise ◽

Dynamical System Identification

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Nonlinear dynamical system identification based on evolutionary interval type-2 TSK fuzzy systems

The 27th Chinese Control and Decision Conference (2015 CCDC) ◽

10.1109/ccdc.2015.7162416 ◽

2015 ◽

Author(s):

Zhang Jianhua ◽

Chen Hongjie ◽

Wang Rubin

Keyword(s):

Dynamical System ◽

System Identification ◽

Fuzzy Systems ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Dynamical System Identification ◽

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Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2015.2513902 ◽

2017 ◽

Vol 28 (1) ◽

pp. 231-243 ◽

Author(s):

Zhao Lu ◽

Jing Sun ◽

Kenneth Butts

Keyword(s):

Dynamical System ◽

System Identification ◽

Projection Operator ◽

Nonlinear Dynamical System ◽

Support Vector ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series

Physical Review E ◽

10.1103/physreve.73.021912 ◽

2006 ◽

Vol 73 (2) ◽

Author(s):

B. A. McKinney ◽

J. E. Crowe ◽

H. U. Voss ◽

P. S. Crooke ◽

N. Barney ◽

...

Keyword(s):

Dynamical System ◽

Time Series ◽

System Identification ◽

Nonlinear Dynamical System ◽

Nonlinear Dynamical ◽

Biological Time ◽

Dynamical System Identification

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Learning performance of a neurocomputer for nonlinear dynamical system identification

Applied Mathematics and Computation ◽

10.1016/s0096-3003(99)00288-x ◽

2001 ◽

Vol 120 (1-3) ◽

pp. 65-77

Author(s):

Masanori Sugisaka ◽

Masayo Nagasaki

Keyword(s):

Dynamical System ◽

System Identification ◽

Nonlinear Dynamical System ◽

Learning Performance ◽

Nonlinear Dynamical ◽

Dynamical System Identification

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Nonlinear dynamical system identification using reduced Volterra models with generalised orthonormal basis functions

Proceedings of the 1997 American Control Conference (Cat. No.97CH36041) ◽

10.1109/acc.1997.612016 ◽

1997 ◽

Author(s):

C. Seretis ◽

E. Zafiriou

Keyword(s):

Dynamical System ◽

System Identification ◽

Orthonormal Basis ◽

Nonlinear Dynamical System ◽

Basis Functions ◽

Nonlinear Dynamical ◽

Volterra Models ◽

Dynamical System Identification

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