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In this paper we present a novel approach for estimating feature-space maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maximizing the likelihood function by repeated line search in the direction of th ...
This work considers sampled data of continuous-domain Gaussian processes. We derive a maximum-likelihood estimator for identifying autoregressive moving average parameters while incorporating the sampling process into the problem formulation. The proposed ...
The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...
Abstract Smartphones collect a wealth of information about their users' environment and activities. This includes GPS (global positioning system) tracks and the MAC (media access control) addresses of devices around the user, and it can go as far as taking ...
We consider multiple description (MD) coding for the Gaussian source with K descriptions under the symmetric mean-squared error (MSE) distortion constraints, and provide an approximate characterization of the rate region. We show that the rate region can b ...
A random variable dominates another random variable with respect to the covariance order if the covariance of any two monotone increas- ing functions of this variable is smaller. We characterize completely the covariance order, give strong sufficient conditi ...
Satellites and ground-based stations have recorded various types of data from the solar-terrestrial system during recent decades. The new type of particle detectors in SEVAN (Space Environmental Viewing and Analysis Network) project will be able to measure ...
Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...
In this paper we propose the use of Discrete Choice Analysis (DCA) for static facial expression classification. Facial expressions are described with expression descriptive units (EDU), consisting in a set of high level features derived from an active appe ...
A new likelihood method to estimate the extremal index, together with an application to temperature data, is presented. Conditions for the validity of the model are discussed and diagnostics are proposed. ...