A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Flexible Independent Component Analysis
Journal of VLSI Signal Processing Systems
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
On the modeling of DCT and subband image data for compression
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Improve maximum likelihood estimation for subband GGD parameters
Pattern Recognition Letters
Modeling the distribution of DCT coefficients for JPEG reconstruction
Image Communication
Asymmetric variate generation via a parameterless dual neural learning algorithm
Computational Intelligence and Neuroscience - Processing of Brain Signals by Using Hemodynamic and Neuroelectromagnetic Modalities
A fast estimation method for the generalized Gaussian mixture distribution on complex images
Computer Vision and Image Understanding
Underdetermined blind source separation based on subspace representation
IEEE Transactions on Signal Processing
EURASIP Journal on Advances in Signal Processing
Bayesian learning of generalized gaussian mixture models on biomedical images
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
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In this contribution, we exploit entropy matching to estimate the exponent parameter of a generalized Gaussian density. Based on this premise, we derive a new entropic expression with respect to higher-order moments of the modeled data, which yields a novel generalized source entropy matching estimator (G-EME). A number of other popular statistical methods are also reviewed, described and compared against the proposed technique. Extensive comparative experimental results illustrate the high accuracy of the proposed estimator, for both light- and heavy-tailed distributions, as well as speech data.