A complex cross-spectral distribution model using Normal Variance Mean Mixtures

We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal density of the Complex Wishart distribution for the cross-spectral density. The Maximum Likelihood estimate of parameters in the distribution is derived, and examples are given from alpha brain wave sources in separated EEG data.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delgado
• Keywords: Corresponding Marginal Density, Cross-spectral Density, ICASSP 2009, Model Density, Signal Processing