A fast learning algorithm for Gabor transformation Ibrahim, Ayman ; Azimi-Sadjadi, Mahmood R. An adaptive learning approach for the computation of the coefficients of the generalized nonorthogonal 2-D Gabor transform representation is introduced in this correspondence. The algorithm uses a recursive least squares (RLS) type algorithm. The aim is to achieve minimum mean squared error for the reconstructed image from the set of the Gabor coefficients. The proposed RLS learning offers better accuracy and faster convergence behavior when compared with the least mean squares (LMS)-based algorithms. Applications of this scheme in image data reduction are also demonstrated. Colorado State University. Libraries 1996 text ; image application/pdf ECEmra00049.pdf FACFECEN100529ARTI eng c1996 IEEE
A fast learning algorithm for Gabor transformation
Ibrahim, Ayman ; Azimi-Sadjadi, Mahmood R.
An adaptive learning approach for the computation of the coefficients of the generalized nonorthogonal 2-D Gabor transform representation is introduced in this correspondence. The algorithm uses a recursive least squares (RLS) type algorithm. The aim is to achieve minimum mean squared error for the reconstructed image from the set of the Gabor coefficients. The proposed RLS learning offers better accuracy and faster convergence behavior when compared with the least mean squares (LMS)-based algorithms. Applications of this scheme in image data reduction are also demonstrated.
Colorado State University. Libraries
1996
text ; image
application/pdf
ECEmra00049.pdf
FACFECEN100529ARTI
eng
c1996 IEEE