In this work a design of a space-varying cellular neural network (CNN) in order to behave as an associative memory is presented. To this purpose, a new class of space-varying cellular neural networks with a nonsymmetric interconnection structure is considered. A stability analysis is firstly carried out. Then, a learning algorithm, based on the relaxation method, is used to compute the feedback parameters of the considered network. Simulation tests are reported to confirm the validity of the suggested approach.
An Approach to the design of Space-varying Cellular Neural Networks for Associative Memories / Brucoli, M.; Carnimeo, L.; Grassi, G.. - STAMPA. - (1994), pp. 549-552. ( 37th Midwest Symposium on Circuits and Systems, MWSCAS'94 Lafayette, LA August 3-5, 1994) [10.1109/MWSCAS.1994.519298].
An Approach to the design of Space-varying Cellular Neural Networks for Associative Memories
M. Brucoli;L. Carnimeo;
1994
Abstract
In this work a design of a space-varying cellular neural network (CNN) in order to behave as an associative memory is presented. To this purpose, a new class of space-varying cellular neural networks with a nonsymmetric interconnection structure is considered. A stability analysis is firstly carried out. Then, a learning algorithm, based on the relaxation method, is used to compute the feedback parameters of the considered network. Simulation tests are reported to confirm the validity of the suggested approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
