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Attractor and ultimate boundedness for stochastic cellular neural networks with delays

✍ Scribed by Li Wan; Qinghua Zhou

Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
207 KB
Volume
12
Category
Article
ISSN
1468-1218

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✦ Synopsis

This paper investigates the attractor and ultimate boundedness for stochastic cellular neural networks with delays. By employing the Lyapunov method and a Lasalle-type theorem, novel results and sufficient criteria on the attractor and ultimate boundedness are obtained.

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✍ Xue Mei Li; Li Hong Huang; Huiyan Zhu πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 138 KB

This paper gives new conditions ensuring global asymptotic stability and global exponential stability for cellular neural networks with constant delay and variable delay, respectively. These conditions are derived by using the essence of piecewise linearity of the output function of cellular neural