Finite-time synchronization for fuzzy neutral-type inertial neural networks with time-varying coefficients and proportional delays

2020 ◽  
Vol 381 ◽  
pp. 51-67 ◽  
Author(s):  
Jigui Jian ◽  
Liyan Duan
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Neutral Type ◽  
Time Varying ◽  
Varying Coefficients ◽  
Proportional Delays ◽  
Inertial Neural Networks ◽  
Time Varying Coefficients

Periodicity of non-autonomous inertial neural networks involving proportional delays and non-reduced order method

2019 ◽  
Vol 12 (02) ◽  
pp. 1950016 ◽  
Author(s):  
Chuangxia Huang ◽  
Hua Zhang
Keyword(s):  
Neural Networks ◽  
Time Varying ◽  
Order Method ◽  
Reduced Order ◽  
Varying Coefficients ◽  
Proportional Delays ◽  
Lyapunov Function Method ◽  
Inertial Neural Networks ◽  
Time Varying Coefficients ◽  
Generalized Exponential Stability

This paper, mainly explores a class of non-autonomous inertial neural networks with proportional delays and time-varying coefficients. By combining Lyapunov function method with differential inequality approach, non-reduced order method is used to establish some novel assertions on the existence and generalized exponential stability of periodic solutions for the addressed model. In addition, an example and its numerical simulations are given to support the proposed approach.

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