Premium
A VLSI‐oriented continuous‐time CNN model
Author(s) -
Espejo S.,
Carmona R.,
DomínguezCastro R.,
RodríguezVázquez A.
Publication year - 1996
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199605/06)24:3<341::aid-cta920>3.0.co;2-l
Subject(s) - very large scale integration , robustness (evolution) , computer science , cellular neural network , electronic circuit , dynamic range , range (aeronautics) , convergence (economics) , algorithm , artificial intelligence , artificial neural network , embedded system , engineering , electrical engineering , aerospace engineering , computer vision , gene , economic growth , economics , biochemistry , chemistry
This paper presents an analysis of the stability and convergence properties of the full signal range (FSR) CNN model. These properties are demonstrated to be similar to those of the Chua‐Yang model and the I/O mapping of known applications is shown to be unaffected by the modification introduced in this new model. In this modified CNN model the dynamic range of the cell state variables equals the dynamic range of the cell output variables and is invariant with the application. This feature results in simpler circuit implementations, thus allowing higher cell densities and improving the robustness of CNN integrated circuits. The FSR CNN model is particularly well suited for programmable CNN integrated circuits.