Ibrahim, Ayman, authorAzimi-Sadjadi, Mahmood R., authorIEEE, publisher2007-01-032007-01-031996Ibrahim, Ayman and Mahmood R. Azimi-Sadjadi, A Fast Learning Algorithm for Gabor Transformation, IEEE Transactions on Image Processing 5, no.1 (January 1996): 171-175.http://hdl.handle.net/10217/848An 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.born digitalarticleseng©1996 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.image representationconvergence of numerical methodslearning systemsadaptive systemstransformsdata compressionleast squares approximationsrecursive estimationdata reductionimage reconstructionText