DocumentCode
3160007
Title
The converging unlearning algorithm for the Hopfield neural network: optimal strategy
Author
Plakhov, A.Yu.
Author_Institution
Inst. of Phys. & Technol., Moscow, Russia
Volume
2
fYear
1994
fDate
9-13 Oct 1994
Firstpage
104
Abstract
The iterative unlearning algorithm converging to the projector (pseudo inverse) rule matrix is studied in the thermodynamical limit. The system of equations describing the spectral evolution of the iterated synaptic matrix is derived. Time-dependent unlearning strength optimizing the convergence of the algorithm is found, the convergence rate being explicitly calculated
Keywords
Hopfield neural nets; Hopfield neural network; convergence; iterated synaptic matrix; iterative unlearning algorithm; projector rule matrix; spectral evolution; thermodynamical limit; Computer aided analysis; Convergence; Equations; Green function; Hopfield neural networks; Iterative algorithms; Physics;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
Conference_Location
Jerusalem
Print_ISBN
0-8186-6270-0
Type
conf
DOI
10.1109/ICPR.1994.576884
Filename
576884
Link To Document