DocumentCode :
1859463
Title :
Discrete-time cellular neural networks for associative memories: a new design method via iterative learning and forgetting algorithms
Author :
Brucoli, Michele ; Carnimeo, Leonarda ; Grassi, Giuseppe
Author_Institution :
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy
Volume :
1
fYear :
1995
fDate :
13-16 Aug 1995
Firstpage :
542
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
Keywords :
cellular neural nets; content-addressable storage; discrete time systems; iterative methods; learning (artificial intelligence); associative memories; discrete-time cellular neural networks; iterative forgetting algorithms; iterative learning algorithms; local connection feature; pattern forgetting; pattern learning; pseudo inverse matrices; Associative memory; Asymptotic stability; Cellular neural networks; Design methodology; Iterative algorithms; Iterative methods; Large-scale systems; Network synthesis; Sparse matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1995., Proceedings., Proceedings of the 38th Midwest Symposium on
Conference_Location :
Rio de Janeiro
Print_ISBN :
0-7803-2972-4
Type :
conf
DOI :
10.1109/MWSCAS.1995.504496
Filename :
504496
Link To Document :
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