DocumentCode
1180256
Title
Iterative methods for solving the Gabor expansion: considerations of convergence
Author
Braithwaite, R. Neil ; Beddoes, Michael P.
Author_Institution
Dept. of Electr. Eng., British Columbia Univ., Vancouver, BC, Canada
Volume
1
Issue
2
fYear
1992
fDate
4/1/1992 12:00:00 AM
Firstpage
243
Lastpage
244
Abstract
J.G. Daugman´s (1988) neural network solution to the Gabor expansion of an image is reformulated as a steepest descent implementation. Nonlinear optimization theory is then applied to select an appropriate convergence factor. Two quasi-Newton-based nonlinear optimization techniques are applied to improve the convergence for certain types of lattice
Keywords
convergence of numerical methods; iterative methods; optimisation; picture processing; Gabor expansion; convergence factor; iterative methods; lattice; neural network solution; nonlinear optimisation theory; quasiNewton nonlinear optimisation; steepest descent implementation; Convergence; Cost function; Eigenvalues and eigenfunctions; Error correction; Frequency; Image sampling; Image storage; Iterative methods; Lattices; Neural networks;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.136600
Filename
136600
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