A design methodology of cellular neural networks (CNN) for heteroassociative and autoassociative memories is presented. A new synthesis procedure of continuous-time CNN for heteroassociative memories is developed, which assures global stability and robustness to the designed networks. A proper representation of discrete-time CNN characterized by multilevel output junctions is introduced to store memory vectors with b-bit length components. The suggested approach provides considerably simple network architectures suitable for VLSI implementation.
Implementation of cellular neural networks for heteroassociative and autoassociative memories / Brucoli, M.; Carnimeo, L.; Grassi, G.. - STAMPA. - (1996), pp. 63-68. (Intervento presentato al convegno 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96 tenutosi a Seville, Spain nel June 24-26, 1996) [10.1109/CNNA.1996.566492].
Implementation of cellular neural networks for heteroassociative and autoassociative memories
M. Brucoli;L. Carnimeo;
1996-01-01
Abstract
A design methodology of cellular neural networks (CNN) for heteroassociative and autoassociative memories is presented. A new synthesis procedure of continuous-time CNN for heteroassociative memories is developed, which assures global stability and robustness to the designed networks. A proper representation of discrete-time CNN characterized by multilevel output junctions is introduced to store memory vectors with b-bit length components. The suggested approach provides considerably simple network architectures suitable for VLSI implementation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
