DocumentCode
1160104
Title
Associative recall using a contraction operator
Author
Stubberud, Allen R. ; Thomas, Robert J.
Author_Institution
Dept. of Electr. Eng., California Univ., Irvine, CA, USA
Volume
36
Issue
5
fYear
1989
fDate
5/1/1989 12:00:00 AM
Firstpage
682
Lastpage
686
Abstract
An associative memory can be defined as a transformation between two sets. Under mild conditions, the associative recall problem can be formulated as that of solving an equation of the form y =f (x ), where y is known and the corresponding value x is not. Here, the associative recall problem is formulated in this way, and conditions on f are developed such that a contraction operator can be developed which solves the given equation. A specific piecewise-linear function is then chosen, and its associative recall properties are discussed. This associative memory is shown to converge rapidly and to have noise rejection properties and some learning capability
Keywords
content-addressable storage; neural nets; associative memory; associative recall problem; contraction operator; converge rapidly; learning capability; noise rejection properties; piecewise-linear function; transformation between two sets; Associative memory; Convergence; Discrete transforms; Equations; Mathematics; Neural networks; Piecewise linear techniques; Problem-solving;
fLanguage
English
Journal_Title
Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0098-4094
Type
jour
DOI
10.1109/31.31316
Filename
31316
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