Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...

Abstract: Markov random field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented using matrix ...

Abstract: Effective noise suppression and data quality enhancement are critical in seismic data processing. Over the years, many traditional and deep learning (DL) methods have been proposed and ...

This repository contains MATLAB scripts and a report for simulating and analyzing Gaussian random variables, focusing on their statistical properties such as mean, variance, and probability density ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...