Robustness analysis of a class of discrete-time systems with applications to neural networks

Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251) ◽

10.1109/acc.1999.782412 ◽

1999 ◽

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Robustness Analysis ◽

Discrete Time Systems ◽

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A joint frequency-position domain structure identification of nonlinear discrete-time systems by neural networks

IEEE Transactions on Automatic Control ◽

10.1109/9.76371 ◽

1991 ◽

Vol 36 (5) ◽

pp. 629-632 ◽

Author(s):

A.M. Elramsisi ◽

M.A. Zohdy ◽

N.K. Loh

Keyword(s):

Neural Networks ◽

Domain Structure ◽

Discrete Time ◽

Structure Identification ◽

Discrete Time Systems ◽

Joint Frequency ◽

Frequency Position ◽

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Adaptive control for a class of nonlinear discrete-time systems using neural networks

Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206) ◽

10.1109/isic.2001.971491 ◽

2002 ◽

Author(s):

S.S. Ge ◽

G.Y. Li ◽

T.H. Lee

Keyword(s):

Neural Networks ◽

Adaptive Control ◽

Discrete Time ◽

Discrete Time Systems ◽

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Robustness analysis of uncertain discrete-time systems with dissipation inequalities and integral quadratic constraints

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.3646 ◽

2016 ◽

Vol 27 (11) ◽

pp. 1940-1962 ◽

Author(s):

Bin Hu ◽

Márcio J. Lacerda ◽

Peter Seiler

Keyword(s):

Discrete Time ◽

Robustness Analysis ◽

Quadratic Constraints ◽

Integral Quadratic Constraints ◽

Discrete Time Systems ◽

Dissipation Inequalities ◽

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Performance robustness analysis of Kalman filter for linear discrete-time systems under plant and noise uncertainty

International Journal of Systems Science ◽

10.1080/00207729508929035 ◽

1995 ◽

Vol 26 (2) ◽

pp. 257-275 ◽

Author(s):

X. F. ZHANG ◽

A. W. HEEMINK ◽

J. C. H. VAN EIJKEREN

Keyword(s):

Kalman Filter ◽

Discrete Time ◽

Robustness Analysis ◽

Noise Uncertainty ◽

Discrete Time Systems ◽

Time Systems ◽

Performance Robustness

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Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks

Chinese Journal of Chemical Engineering ◽

10.1016/s1004-9541(08)60230-x ◽

2009 ◽

Vol 17 (3) ◽

pp. 454-459 ◽

Author(s):

Yan ZHANG ◽

Xiuxia LIANG ◽

Peng YANG ◽

Zengqiang CHEN ◽

Zhuzhi YUAN

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Modeling And Control ◽

Discrete Time Systems ◽

And Control ◽

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Identification of nonlinear discrete time systems using trigonometric polynomial neural networks

2008 International Conference on Control, Automation and Systems ◽

10.1109/iccas.2008.4694672 ◽

2008 ◽

Author(s):

Yoshihiro Yamamoto

Keyword(s):

Neural Networks ◽

Trigonometric Polynomial ◽

Discrete Time ◽

Discrete Time Systems ◽

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Adaptive control of a class of nonlinear discrete-time systems using hybrid neural networks

1997 European Control Conference (ECC) ◽

10.23919/ecc.1997.7082145 ◽

1997 ◽

Author(s):

T.L. Liao ◽

J.H. Horng

Keyword(s):

Neural Networks ◽

Adaptive Control ◽

Discrete Time ◽

Discrete Time Systems ◽

Time Systems ◽

Hybrid Neural Networks

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New sufficient condition of Discrete-time systems of neural networks

American Journal of Applied Sciences ◽

10.3844/ajassp.2011.113.115 ◽

2011 ◽

Vol 8 (2) ◽

pp. 113-115

Author(s):

Tanusit

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Sufficient Condition ◽

Discrete Time Systems ◽

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Structure recognition of nonlinear discrete-time systems by neural networks

10.1109/icsmc.1989.71469 ◽

2003 ◽

Author(s):

A.M. Elramsisi ◽

M.A. Zohdy ◽

N.K. Loh

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Discrete Time Systems ◽

Structure Recognition ◽

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Stability robustness analysis of discrete-time systems with multiple large parameter variations

10.1016/0005-1098(94)90038-8 ◽

1994 ◽

Vol 30 (2) ◽

pp. 357-361 ◽

Author(s):

Mansour Eslami

Keyword(s):

Discrete Time ◽

Robustness Analysis ◽

Large Parameter ◽

Stability Robustness ◽

Discrete Time Systems ◽

Parameter Variations ◽

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