Hilger-type impulsive differential inequality and its application to impulsive synchronization of delayed complex networks on time scales

2018 ◽  
Vol 61 (7) ◽  
Author(s):  
Zhenkun Huang ◽  
Jinde Cao ◽  
Youssef N. Raffoul
Keyword(s):  
Complex Networks ◽  
Time Scales ◽  
Differential Inequality ◽  
Impulsive Synchronization ◽  
Impulsive Differential Inequality

Impulsive synchronization of complex networks with non-delayed and delayed coupling

2009 ◽  
Vol 373 (46) ◽  
pp. 4255-4259 ◽  
Author(s):  
Song Zheng ◽  
Gaogao Dong ◽  
Qinsheng Bi
Keyword(s):  
Complex Networks ◽  
Impulsive Synchronization ◽  
Delayed Coupling

Delayed impulsive synchronization of discrete-time complex networks with distributed delays

2015 ◽  
Vol 82 (4) ◽  
pp. 2081-2096 ◽  
Author(s):  
Zhen Li ◽  
Jian-an Fang ◽  
Wenbing Zhang ◽  
Xin Wang
Keyword(s):  
Complex Networks ◽  
Discrete Time ◽  
Distributed Delays ◽  
Impulsive Synchronization

scholarly journals Growth and Optimality in Network Evolution

2011 ◽  
Vol 17 (4) ◽  
pp. 281-291 ◽  
Author(s):  
Markus Brede
Keyword(s):  
Complex Networks ◽  
Time Scales ◽  
Power Law ◽  
Path Length ◽  
Network Evolution ◽  
Hierarchical Organization ◽  
Optimization Process ◽  
Assembly Process ◽  
Rich Variety ◽  
Mixing Patterns

We investigate networks whose evolution is governed by the interaction of a random assembly process and an optimization process. In the first process, new nodes are added one at a time and form connections to randomly selected old nodes. In between node additions, the network is rewired to minimize its path length. For time scales at which neither the assembly nor the optimization processes are dominant, we find a rich variety of complex networks with power law tails in the degree distributions. These networks also exhibit nontrivial clustering, a hierarchical organization, and interesting degree-mixing patterns.

scholarly journals Almost anti-periodic solution of inertial neural networks model on time scales

2022 ◽  
Vol 355 ◽  
pp. 02006
Author(s):  
Adnène Arbi ◽  
Najeh Tahri
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Lyapunov Function ◽  
Time Scales ◽  
Differential Inequality ◽  
Function Method ◽  
Lyapunov Function Method ◽  
Existence And Stability ◽  
Inertial Neural Networks ◽  
Inequality Techniques

In this work, since the importance of investigation of oscillators solutions, an methodology for proving the existence and stability of almost anti-periodic solutions of inertial neural networks model on time scales are discussed. By developing an approach based on differential inequality techniques coupled with Lyapunov function method. A numerical example is given for illustration.

scholarly journals Global Stability of Delayed Ecosystem via Impulsive Differential Inequality and Minimax Principle

2021 ◽  
Author(s):  
Ruofeng Rao
Keyword(s):  
Global Stability ◽  
Stationary Solution ◽  
Differential Inequality ◽  
Impulsive Control ◽  
Stationary Solutions ◽  
Delayed Feedback ◽  
Competition Model ◽  
Minimax Principle ◽  
Impulsive Differential Inequality

This paper reports applying Minimax principle and impulsive differential inequality to derive the existence of multiple stationary solutions and the global stability of a positive stationary solution for a delayed feedback Gilpin-Ayala competition model with impulsive disturbance. The conclusion obtained in this paper reduces the conservatism of the algorithm compared with the known literature, for the impulsive disturbance is not limited to impulsive control.

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