Simultaneous autoregressive models for spatial extremes
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Frequency Domain Linear Prediction (FDLP) represents the technique for approximating temporal envelopes of a signal using autoregressive models. In this paper, we propose a wide-band audio coding system exploiting FDLP. Specifically, FDLP is applied on cri ...
Frequency Domain Linear Prediction (FDLP) represents the technique for approximating temporal envelopes of a signal using autoregressive models. In this paper, we propose a wide-band audio coding system exploiting FDLP. Specifically, FDLP is applied on cri ...
In this paper the perturbation influence properties of the stochastic model (variance-covariance) in linear models is discussed in detail. Some very useful formulae are established about the variance-covariance perturbation influence on the model parameter ...
A non-parametric method of distribution estimation for univariate data is presented. The idea is to adapt the smoothing spline procedure used in regression to the estimation of distributions via a scatterplot smoothing of theempirical distribution function ...
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...
Mixture models form the essential basis of data clustering within a statistical framework. Here, the estimation of the parameters of a mixture of Gaussian densities is considered. In this particular context, it is well known that the maximum likelihood app ...
Rapid evaluation and design space exploration at the algorithmic level are important issues in the design cycle. In this paper we propose an original area vs delay estimation methodology that targets reconfigurable architectures. Two main steps compose the ...
This communication presents a nonsupervised three-dimensional segmentation method based upon a discrete-level unilateral Markov field model for the labels and conditionally Gaussian densities for the observed voxels. Such models have been shown to yield nu ...
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 ...
The quality of multivariate calibration (MVC) models obtained depends on the effective treatment of errors in spectral data. If errors in different absorbance measurements are correlated and have different variances, then the Maximum Likelihood Principal C ...
