Title :
Convergence and stability of the FSR CNN model
Author :
Espejo, S. ; Rodriguez-Vazquez, Angel ; Dominguez-Castro, R. ; Carmona, R.
Author_Institution :
Centro Nacional de Microelectron., Seville Univ., Spain
Abstract :
Stability and convergency results are reported for a modified continuous-time CNN model. The signal range of the state variables is equal to the unitary interval, independently of the application, Stability and convergency properties are similar to those of the original model and, for given templates and offset coefficients. The results are generally identical. In addition, robustness and area-efficiency of VLSI implementations are significantly advantageous
Keywords :
cellular neural nets; convergence; stability; FSR CNN; cellular neural nets; convergency; modified continuous-time CNN model; stability; state variables; Boundary conditions; Cellular neural networks; Convergence; Equations; Stability; State feedback;
Conference_Titel :
Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
Conference_Location :
Rome
Print_ISBN :
0-7803-2070-0
DOI :
10.1109/CNNA.1994.381640
