Bayesian operational modal analysis based on the expectation-maximization algorithm.

Gaussian Mixture Model for Clustering

matlab code for exponential family harmoniums, RBMs, DBNs, and relata

EM learning for a mixture of K multivariate Bernoullis with binary images

A new take on EEG sleep spindles detection exploiting a generative model (dynamic bayesian network) to characterize reoccurring dynamical regimes of single-channel EEG.

Using Statistical Learning Method to Segment Image

Image segmentation using the EM algorithm that relies on a GMM for intensities and a MRF model on the labels. Based on "Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm" (Zhang, Y et al.)

MATLAB codes for paper: Tractable Maximum Likelihood Estimation for Latent Structure Influence Models with Applications to EEG & ECoG processing

Package in Matlab for generating Synthatic Data using GMM and EM Clustering on that

Fast Expectation Maximization (EM) algorithm for weighted samples in MATLAB

SON-EM - Algorithm for parameter estimation of hybrid time-varying parameter systems using Sum of Norms regularization and Expectation Maximization

Finding homogenous regions in the Salinas hyperspectral image

An Implementation of Markov Switching Models for Weather Derivative Pricing

Inference in Gaussian models with missing data using Equalisation Maximisation

Training a hidden Markov model through expectation-maximization, using Baum-Welch formulae, for applications in speech recognition

Implementation of EM algorithm for the Gaussian mixture model.

My Master's Thesis Project at IIT Kharagpur, (May'24 - June'25), [Place: IPCV Lab, E&ECE, IIT Kharagpur]

Matlab code with examples of algorithms I'm learning/testing

The Expectation Maximization (EM) algorithm is used to reduce Poisson noise in CT images. The repository provides derivations and evaluations with the Cramer-Rao Lower Bound (CRLB).