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;
1996-01-01
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.File in questo prodotto:
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