DocumentCode :
2730130
Title :
Novelty detection on a very large number of memories stored in a Hopfield-style network
Author :
Jagota, Arun
Author_Institution :
Dept. of Comput. Sci., State Univ. of New York, Buffalo, NY, USA
fYear :
1991
fDate :
8-14 Jul 1991
Abstract :
Summary form only given, as follows. The Hopfield-style network does not forget any stored memory. Its error-correcting performance, however, degrades rapidly with a large number of stored memories because of the rapid development of spurious memories. The author shows that in spite of this, the network performs well in the case of error detection, specifically novelty detection, even on very large collections of stored memories. The speed with which the network can detect novelty, even on very large collections of stored memories, is the main advantage of this scheme. Efficient distributed storage of large collections of memories is another important advantage
Keywords :
content-addressable storage; error detection; neural nets; Hopfield-style network; distributed storage; error detection; error-correcting performance; novelty detection; spurious memories; stored memory; very large collections; Computer errors; Computer science; Degradation; Electrical equipment industry; Industrial control; Intelligent networks; Management training; Pattern recognition; Quality control; Quality management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
Type :
conf
DOI :
10.1109/IJCNN.1991.155491
Filename :
155491
Link To Document :
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