DocumentCode :
2496689
Title :
Investigation of generalized Hopfield model by statistical physics methods
Author :
Kryzhanovsky, Boris V. ; Litinskii, Leonid B.
Author_Institution :
Center of Opt. Neural Technol., Russian Acad. of Sci., Moscow, Russia
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
6
Abstract :
The proposed generalization of the Hopfield model consists in assigning different weight coefficients to input patterns that are used to construct the Hebb connection matrix. Application of statistical physics methods to such a system gives unexpected results even for the simplest variant of differences of weight coefficients. Namely, there are unusual behaviors of the critical value of the load parameter and of the overlap of the state with the pattern.
Keywords :
Hopfield neural nets; generalisation (artificial intelligence); matrix algebra; statistical analysis; Hebb connection matrix; generalized Hopfield model; statistical physics methods; Analytical models; Associative memory; Character recognition; Equations; Mathematical model; Physics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596872
Filename :
5596872
Link To Document :
بازگشت