Star-CNN is a particular architecture of Cellular Neural Networks that has been recently proposed. This dynamic nonlinear system is defined by connecting N identical dynamical sysstem called local cell with a Central System in the shape of a star. Each of the local cells communicates with others through the Central System. Because of the hardware requirements of such a system, its implementation comes out extremely expansive from the silicon area occupation point of view. This paper presents a hardwaare implementation of this new CNN architecture based on a time division approach that allows to significantly reduce the silicon area occupation by minimizing the number of the analogue multipliers. © 2008 IEEE.
Sargeni, F., Bonaiuto, V., Bonifazi, M. (2006). Multiplexed circuit for star-CNN architecture. In Proceedings of the 2006 10th IEEE international workshop on cellular neural networks and their applications (pp.191-195). New York : IEEE [10.1109/CNNA.2006.341628].
Multiplexed circuit for star-CNN architecture
SARGENI, FAUSTO;BONAIUTO, VINCENZO;
2006-01-01
Abstract
Star-CNN is a particular architecture of Cellular Neural Networks that has been recently proposed. This dynamic nonlinear system is defined by connecting N identical dynamical sysstem called local cell with a Central System in the shape of a star. Each of the local cells communicates with others through the Central System. Because of the hardware requirements of such a system, its implementation comes out extremely expansive from the silicon area occupation point of view. This paper presents a hardwaare implementation of this new CNN architecture based on a time division approach that allows to significantly reduce the silicon area occupation by minimizing the number of the analogue multipliers. © 2008 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
