Existence and uniqueness of periodic solutions of nonautonomous cellular neural networks with impulses

Gui, Zhanji; Ge, Weigao

doi:10.1016/j.physleta.2006.01.018

Cited by 42 publications

(33 citation statements)

References 35 publications

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“…The Hopfield neural networks with impulse effect are studied, where the criteria on the existence, uniqueness and global stability of periodic solution are obtained. Further, Gui chaos strange attractor was also found [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 79%

“…As is known to all that (1) can exhibit chaotic phenomenons [6][7][8][9][10] . In order to show it clearly, we give the following example.…”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

“…According to Theorems 1 and 2 in [6], the cellular neural network model (2) has a unique 2S -periodic solution with 5-impulses in a period. Furthermore, if 1 T , then (H2) isn't satisfied.…”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

“…Taking (2) as the drive system in Example 1. The response system is constructed as follows: Then the error system of drive system (2) and respond system (9) is constructed as follows: Numeric results show that system (9) still has a Gui chaotic strange attractor [6][7][8][9][10] . The phase plot of Gui chaotic strange attractor of response system is shown in Fig.…”

Section: A Simulation Examplementioning

confidence: 99%

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Exponential Synchronization of the Hopfield Neural Networks with New Chaotic Strange Attractor

Gui¹,

Wang

2017

ITM Web Conf.

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Abstract-This paper studies the problems of exponential synchronization for the Hopfield neural networks with impulsive effects and Gui chaotic strange attractor. By employing the Lyapunov functional method of impulsive functional differential equations, some criteria for synchronization between two impulsive neural networks are derived. An illustrative example is provided to show the effectiveness and feasibility of the proposed method and results.

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