DocumentCode
1906163
Title
Training a Hopfield memory with noisy examples
Author
Segura, Enrique Carlos
Author_Institution
Consejo Nacional de Investigaciones Cientificas y Tecnicas, Buenos Aires, Argentina
fYear
1993
fDate
1993
Firstpage
1075
Abstract
The ability of the Hopfield model of associative memory to learn from examples in the presence of noise is studied. Properties concerning this ability are discussed. Computer simulations to test these results experimentally are presented
Keywords
Hopfield neural nets; content-addressable storage; learning (artificial intelligence); Hopfield model; Hopfield neural nets; associative memory; learning; noise; Associative memory; Computer networks; Computer simulation; Distributed computing; Hebbian theory; Neural networks; Neurons; Random variables; Statistical distributions; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298707
Filename
298707
Link To Document