Ica and iva bounded multivariate generalized gaussian mixture based hidden markov models

AH Al-gumaei, M Azam, M Amayri… - Engineering Applications of …, 2023‏ - Elsevier
Abstract Machine learning (ML), a branch of artificial intelligence (AI), is an area of
computational science that is concerned with the analysis and interpretation of patterns and …

Novel approach for ECG separation using adaptive constrained IVABMGGMM

A Algumaei, M Azam, N Bouguila - Digital Signal Processing, 2024‏ - Elsevier
In this paper, we introduce the constrained independent vector analysis integrated with the
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …

Bounded asymmetric gaussian mixture-based hidden markov models

Z **an, M Azam, M Amayri, W Fan… - Hidden Markov models and …, 2022‏ - Springer
Abstract Hidden Markov models (HMMs) have been widely applied in machine learning to
model diversified and heterogeneous time series data. In this chapter, integration of the …

Bounded Support Finite Mixtures for Multidimensional Data Modeling and Clustering

M Azam - 2019‏ - spectrum.library.concordia.ca
Data is ever increasing with today's many technological advances in terms of both quantity
and dimensions. Such inflation has posed various challenges in statistical and data analysis …

Mixture-Based Clustering and Hidden Markov Models for Energy Management and Human Activity Recognition: Novel Approaches and Explainable Applications

HGA Al-Bazzaz - 2023‏ - spectrum.library.concordia.ca
In recent times, the rapid growth of data in various fields of life has created an immense
need for powerful tools to extract useful information from data. This has motivated …

Generative Models Based on the Bounded Asymmetric Gaussian Distribution

Z **an - 2021‏ - spectrum.library.concordia.ca
The bounded asymmetric Gaussian mixture model (BAGMM) has proved that it generally
performs better than the classical Gaussian mixture model. In this thesis, we investigate the …

Bayesian inference of hidden markov models using dirichlet mixtures

RT Vemuri, M Azam, Z Patterson… - Hidden Markov Models and …, 2012‏ - Springer
In this chapter, we propose an efficient unsupervised learning approach following a
Bayesian framework for Hidden Markov Model (HMM) learning. We showcase a unique …