Globally Exponential Stability and Globally Power Stability of Quaternion-Valued Neural Networks With Discrete and Distributed Delays Article Swipe

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Huiling Duan , Tao Peng , Zhengwen Tu , Jianlong Qiu , Jianquan Lu ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.1109/access.2020.2978647

This paper investigates the stability of a class of quaternion-valued neural networks (QVNNs) with discrete and distributed delays. By decomposing the QVNN and forming an equivalent real-valued vector-matrix differential equation (RVVDE), based on the Lyapunov theory and some matrix inequalities, some sufficient conditions are derived to ensure the existence and uniqueness, the globally exponential stability and the globally power stability of the equilibrium of RVVDE. These conditions also apply to the QVNN. Two numerical examples are given to show the advantage and the effectiveness of the main results.

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Exponential stability Quaternion Mathematics Uniqueness Control theory (sociology) Stability (learning theory) Applied mathematics Artificial neural network Lyapunov function Stability theory Lyapunov stability Matrix (chemical analysis) Computer science Mathematical analysis Nonlinear system Artificial intelligence Physics Quantum mechanics Machine learning Control (management) Materials science Geometry Composite material

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Type: article
Language: en
Landing Page: https://doi.org/10.1109/access.2020.2978647
PDF: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09025069.pdf
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Cited By: 8
References: 40
Related Works: 10
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DOI: https://doi.org/10.1109/access.2020.2978647

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Title: Globally Exponential Stability and Globally Power Stability of Quaternion-Valued Neural Networks With Discrete and Distributed Delays

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Language: en

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Publication year: 2020

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Publication date: 2020-01-01

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Authors: Huiling Duan, Tao Peng, Zhengwen Tu, Jianlong Qiu, Jianquan Lu

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Landing page: https://doi.org/10.1109/access.2020.2978647

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Concepts: Exponential stability, Quaternion, Mathematics, Uniqueness, Control theory (sociology), Stability (learning theory), Applied mathematics, Artificial neural network, Lyapunov function, Stability theory, Lyapunov stability, Matrix (chemical analysis), Computer science, Mathematical analysis, Nonlinear system, Artificial intelligence, Physics, Quantum mechanics, Machine learning, Control (management), Materials science, Geometry, Composite material

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Cited by: 8

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