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

fYear

1994

fDate

18-21 Dec 1994

Firstpage

411

Lastpage

416

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CNNA.1994.381640

Filename

381640

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2515899