Title :
Robust stability of uncertain cellular neural network for image processing - an LMI approach
Author :
Su, Te-Jen ; Hsueh, Hung-Hsin ; Su, Yi-Hui
Author_Institution :
Center for Electron. Commun. Technol., Nat. Kaohsiung Univ. of Appl. Sci., Taiwan
Abstract :
In this paper, a network called a discrete-time cellular neural network (DTCNN) with uncertainty is introduced. A methodology for the robust stability of the DTCNN is presented. The uncertainties are assumed to be norm-bounded. The methodology is based on the Lyapunov functional combining with linear matrix inequality (LMI) approach. An example is provided to illustrate the effectiveness of the proposed methodology.
Keywords :
Lyapunov methods; cellular neural nets; image processing; linear matrix inequalities; stability; uncertain systems; Lyapunov functional; discrete-time cellular neural network; image processing; linear matrix inequality; robust stability; uncertain cellular neural network; Cellular neural networks; Circuit noise; Communications technology; Equations; Image processing; Information management; Linear matrix inequalities; Output feedback; Robust stability; Uncertainty; discrete-time cellular neural network; linear matrix inequality; robust stability;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
Print_ISBN :
0-7803-9185-3
DOI :
10.1109/CNNA.2005.1543157
