Abstract
A generalized Gaussian model for correlated signal sources is introduced. The probability density function of a first-order autoregressive process driven by generalized Gaussian white noise is approximated by a generalized Gaussian probability density function. The interdependence between the correlation coefficient and the shape parameter of the first-order autoregressive process and the shape parameter of the driving noise is investigated. Application of the proposed method for modeling of probability density functions of transform and subband coefficients is considered.
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