Iterative methods for solving the Gabor expansion: considerations of convergence
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Updated: Jul 7, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
1Dept. of Electr. Eng., British Columbia Univ., Vancouver, BC.
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.
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