Xiang, Hong; Yan, Ke-Ming; Wang, Bai-Yan Existence and global stability of periodic solution for delayed discrete high-order Hopfield-type neural networks. (English) Zbl 1135.39008 Discrete Dyn. Nat. Soc. 2005, No. 3, 281-297 (2005). Summary: By using coincidence degree theory as well as a priori estimates and Lyapunov functional, we study the existence and global stability of periodic solution for discrete delayed high-order Hopfield-type neural networks. We obtain some easily verifiable sufficient conditions to ensure that there exists a unique periodic solution, and all theirs solutions converge to such a periodic solution. Cited in 14 Documents MSC: 39A11 Stability of difference equations (MSC2000) 37N25 Dynamical systems in biology 82C32 Neural nets applied to problems in time-dependent statistical mechanics 92B20 Neural networks for/in biological studies, artificial life and related topics Keywords:difference equation; coincidence degree theory; Lyapunov functional; global stability; periodic solution; discrete delayed high-order Hopfield-type neural network PDFBibTeX XMLCite \textit{H. Xiang} et al., Discrete Dyn. Nat. Soc. 2005, No. 3, 281--297 (2005; Zbl 1135.39008) Full Text: DOI EuDML