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Future work will include biological dynamic systems based on impulsive differential equations [25, 26].
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Based on impulsive stability theory, we design proper impulsive controllers and derive some sufficient conditions for achieving synchronization.
Based on an impulsive differential inequality, the properties of random variables, the framework of Filippov solution, and Lyapunov functional method, sufficient conditions are derived to guarantee that the considered coupled memristor-based neural networks can be pth moment globally exponentially synchronized onto an isolated node under both of the two classes of hybrid impulsive controllers.
Our method is based on impulsive-integral inequalities.
There are many physical phenomena that are described by means of impulsive differential equations, for instance, biological systems, electrical engineering, chemical reactions, among others can be modeled by impulsive differential equations, a good survey on impulsive differential equations can be found in [1] see also [2, 3].
Interested readers may consult the monograph [11] for more details on impulsive differential equations.
For most research papers on impulsive differential equation BVPs, see [16 19] and the references therein.
For some monographs on impulsive differential equations we refer to [16 18].
As usual, see any of the references on impulsive differential equations, we consider the Banach space (4.1).
For some recent work on impulsive differential equations of fractional order, see [26 31] and the references therein.
Since the end of last century, many authors including Professors Nieto and Hernández pay great attention on impulsive differential systems.
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