A varying-gain recurrent neural-network with super exponential convergence rate for solving nonlinear time-varying systems

Neurocomputing ◽

10.1016/j.neucom.2019.04.002 ◽

2019 ◽

Vol 351 ◽

pp. 10-18

Author(s):

Zhijun Zhang ◽

Xiaolu Yang ◽

Xianzhi Deng ◽

Lingao Li

Keyword(s):

Neural Network ◽

Convergence Rate ◽

Recurrent Neural Network ◽

Exponential Convergence ◽

Time Varying ◽

Exponential Convergence Rate ◽

Time Varying Systems

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Estimation of attraction domain and exponential convergence rate of Hopfield-type associative memory neural network

Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527) ◽

10.1109/wcica.2002.1021529 ◽

2003 ◽

Author(s):

Guanghui Cai ◽

Jihong Shi

Keyword(s):

Neural Network ◽

Convergence Rate ◽

Associative Memory ◽

Exponential Convergence ◽

Attraction Domain ◽

Exponential Convergence Rate

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Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay

Chaos Solitons & Fractals ◽

10.1016/j.chaos.2005.04.014 ◽

2005 ◽

Vol 26 (5) ◽

pp. 1499-1505 ◽

Author(s):

Fenghua Tu ◽

Xiaofeng Liao

Keyword(s):

Neural Networks ◽

Convergence Rate ◽

Exponential Stability ◽

Exponential Convergence ◽

Time Varying ◽

Time Varying Delay ◽

Exponential Convergence Rate ◽

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On-line neural network learning algorithm with exponential convergence rate

Electronics Letters ◽

10.1049/el:19960895 ◽

1996 ◽

Vol 32 (15) ◽

pp. 1381 ◽

Author(s):

Y. Zhao

Keyword(s):

Neural Network ◽

Convergence Rate ◽

Exponential Convergence ◽

Learning Algorithm ◽

Neural Network Learning ◽

Network Learning ◽

Exponential Convergence Rate ◽

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Globally Exponential Stability Analysis and Estimation of the Exponential Convergence Rate for Neural Networks with Multiple Time Varying Delays

Lecture Notes in Computer Science - Advances in Natural Computation ◽

10.1007/11539087_8 ◽

2005 ◽

pp. 61-70 ◽

Author(s):

Huaguang Zhang ◽

Zhanshan Wang

Keyword(s):

Neural Networks ◽

Stability Analysis ◽

Convergence Rate ◽

Exponential Stability ◽

Exponential Convergence ◽

Multiple Time ◽

Time Varying ◽

Exponential Convergence Rate ◽

Globally Exponential Stability

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Estimate of exponential convergence rate in total variation by spectral gap

Acta Mathematica Sinica English Series ◽

10.1007/bf02563878 ◽

1998 ◽

Vol 14 (1) ◽

pp. 9-16 ◽

Author(s):

Chen Mufa

Keyword(s):

Convergence Rate ◽

Total Variation ◽

Spectral Gap ◽

Exponential Convergence ◽

Exponential Convergence Rate

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Novel Recurrent Neural Network for Time-Varying Problems Solving [Research Frontier]

IEEE Computational Intelligence Magazine ◽

10.1109/mci.2012.2215139 ◽

2012 ◽

Vol 7 (4) ◽

pp. 61-65 ◽

Author(s):

Dongsheng Guo ◽

Yunong Zhang

Keyword(s):

Neural Network ◽

Recurrent Neural Network ◽

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A New Varying-Parameter Recurrent Neural-Network for Online Solution of Time-Varying Sylvester Equation

IEEE Transactions on Cybernetics ◽

10.1109/tcyb.2017.2760883 ◽

2018 ◽

Vol 48 (11) ◽

pp. 3135-3148 ◽

Author(s):

Zhijun Zhang ◽

Lunan Zheng ◽

Jian Weng ◽

Yijun Mao ◽

Wei Lu ◽

...

Keyword(s):

Neural Network ◽

Recurrent Neural Network ◽

Sylvester Equation ◽

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Design and Analysis of a General Recurrent Neural Network Model for Time-Varying Matrix Inversion

IEEE Transactions on Neural Networks ◽

10.1109/tnn.2005.857946 ◽

2005 ◽

Vol 16 (6) ◽

pp. 1477-1490 ◽

Author(s):

Y. Zhang ◽

S.S. Ge

Keyword(s):

Neural Network ◽

Network Model ◽

Recurrent Neural Network ◽

Neural Network Model ◽

Matrix Inversion ◽

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Solving discrete time-varying complex division using recurrent neural network with disturbance suppression

10.23919/icac50006.2021.9594070 ◽

2021 ◽

Author(s):

Yang Shi ◽

Wenhan Zhao ◽

Jie Wang ◽

Jian Li ◽

Dimitrios K. Gerontitis

Keyword(s):

Neural Network ◽

Discrete Time ◽

Recurrent Neural Network ◽

Time Varying ◽

Disturbance Suppression

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Super Exponentially Convergent Approximation to the Solution of the Schrödinger Equation in Abstract Setting

Computational Methods in Applied Mathematics ◽

10.2478/cmam-2010-0020 ◽

2010 ◽

Vol 10 (4) ◽

pp. 345-358 ◽

Author(s):

I.P. Gavrilyuk

Keyword(s):

Schrödinger Equation ◽

Convergence Rate ◽

Schrodinger Equation ◽

Exponential Convergence ◽

Exponential Convergence Rate ◽

Abstract Setting

AbstractWe have developed an approximation to the solution of the Schrödinger equation in abstract setting. The accuracy of our approximation depends on the smoothness of this solution. We show that for the analytical initial vectors our approximation possesses a super exponential convergence rate.

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