Title :
Programmable non-linearity for STAR cellular neural networks
Author :
Sargeni, Fausto ; Bonaiuto, Vincenzo
Author_Institution :
Dept. of Electron. Eng., Univ. of Rome Tor Vergata, Rome, Italy
Abstract :
The implementation of a feasible circuital solution for modeling complex systems as STAR cellular neural networks requires circuits with features and performances tailored for the specific application. In particular, this paper deals with the design of a current mode digitally programmable non-linearity that has been properly developed for a "time-division architecture" implementation of a first order STAR CNN system.
Keywords :
cellular neural nets; integrated circuit design; integrated circuit modelling; logic design; programmable circuits; STAR CNN system; STAR cellular neural network; circuital solution; complex system modeling; current mode digitally programmable nonlinearity; time-division architecture; Cellular neural networks; Circuits; Digital control; Filtering algorithms; Mirrors; Silicon; Switches; Time division multiple access; Transconductance; Voltage control;
Conference_Titel :
Circuit Theory and Design, 2009. ECCTD 2009. European Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-3896-9
Electronic_ISBN :
978-1-4244-3896-9
DOI :
10.1109/ECCTD.2009.5275039
