Title :
Training a Hopfield memory with noisy examples
Author :
Segura, Enrique Carlos
Author_Institution :
Consejo Nacional de Investigaciones Cientificas y Tecnicas, Buenos Aires, Argentina
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;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298707
