Existence and Global Stability of a Periodic Solution for Discrete-Time Cellular Neural Networks. (10th December 2012)

• Record Type: Journal Article
• Authors: Shao, Haijian; Wei, Haikun; Wang, Haoxiang
• Other Names: Wong Kwok-Wo Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2012(2012)
• Publication Date: 2012-12-10
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2012/645214
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : A novel sufficient condition is developed to obtain the discrete-time analogues of cellular neural network (CNN) with periodic coefficients in the three-dimensional space. Existence and global stability of a periodic solution for the discrete-time cellular neural network (DT-CNN) are analysed by utilizing continuation theorem of coincidence degree theory and Lyapunov stability theory, respectively. In addition, an illustrative numerical example is presented to verify the effectiveness of the proposed results.