DocumentCode
814467
Title
Discrete-time cellular neural networks for associative memories with learning and forgetting capabilities
Author
Brucoli, Michele ; Carnimeo, Leonarda ; Grassi, Giuseppe
Author_Institution
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy
Volume
42
Issue
7
fYear
1995
fDate
7/1/1995 12:00:00 AM
Firstpage
396
Lastpage
399
Abstract
A synthesis procedure for associative memories using Discrete-Time Cellular Neural Networks (DTCNN´s) with learning and forgetting capabilities is presented. The proposed design technique generates networks with the capability of learning new patterns and forgetting old ones without recomputing the whole interconnection matrix and the input vector
Keywords
cellular neural nets; content-addressable storage; discrete time systems; learning (artificial intelligence); stability; associative memories; discrete-time cellular neural networks; forgetting capabilities; interconnection matrix; learning capabilities; stability analysis; synthesis procedure; Artificial neural networks; Associative memory; Cellular neural networks; Design methodology; Hopfield neural networks; Network synthesis; Neural networks; Sparse matrices; Stability analysis; Very large scale integration;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/81.401156
Filename
401156
Link To Document