DocumentCode
1287315
Title
Neural-net inference and content addressable memory
Author
Mazza, Christian
Author_Institution
Section de Math., Geneva, Switzerland
Volume
8
Issue
1
fYear
1997
fDate
1/1/1997 12:00:00 AM
Firstpage
133
Lastpage
140
Abstract
We consider Whittle´s probabilistic content addressable memory, the antiphon, which is designed for recovering stored patterns from nonlinear distortions of the input messages. We give an application to content-based image retrieval systems and propose canonical ways of choosing similarity thresholds ensuring statistical consistency
Keywords
content-addressable storage; inference mechanisms; neural nets; probability; antiphon; content-based image retrieval systems; neural-net inference; nonlinear distortions; probabilistic content-addressable memory; similarity thresholds; statistical consistency; Associative memory; Content based retrieval; Hebbian theory; Hopfield neural networks; Hypercubes; Image retrieval; Maximum likelihood decoding; Neural networks; Quantum computing; Testing;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.554197
Filename
554197
Link To Document