2007/05/16 by Ali Mohammad-Djafari, Mohammad-Djafari, Ali
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Statistics and Probability (physics.data-an) #physics.data-an
paper · pdf · doi:10.48550/arxiv.0705.2454
8 pages. This paper is submitted to ICA2007
arxiv created 2007/05/16 · arxiv updated 2009/12/01
Modeling non Gaussian and non stationary signals and images has always been one of the most important part of signal and image processing methods. In this paper, first we propose a few new models, all based on using hidden variables for modeling either stationary but non Gaussian or Gaussian but non stationary or non Gaussian and non stationary signals and images. Then, we will see how to use these models in independent component analysis (ICA) or blind source separation (BSS). The computational aspects of the Bayesian estimation framework associated with these prior models are also discussed.