In this paper a synthesis procedure of discrete-time Cellular Neural Networks (DTCNN's) for associative memories with iterative learning and forgetting algorithms is developed, by which each pattern to be stored is learnt one at a time and each pattern to be forgotten is deleted one at a time. The proposed approach exploits the properties of pseudo inverse matrices and preserves the local connection feature of DTCNN's.

Discrete-time cellular neural networks for associative memories: a new design method via iterative learning and forgetting algorithms

M. Brucoli;L. Carnimeo;
1996

Abstract

In this paper a synthesis procedure of discrete-time Cellular Neural Networks (DTCNN's) for associative memories with iterative learning and forgetting algorithms is developed, by which each pattern to be stored is learnt one at a time and each pattern to be forgotten is deleted one at a time. The proposed approach exploits the properties of pseudo inverse matrices and preserves the local connection feature of DTCNN's.
38th Midwest Symposium on Circuits and Systems, MWSCAS'95
0-7803-2972-4
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/18056
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