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Ica and iva bounded multivariate generalized gaussian mixture based hidden markov models
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 …
computational science that is concerned with the analysis and interpretation of patterns and …
Novel approach for ECG separation using adaptive constrained IVABMGGMM
In this paper, we introduce the constrained independent vector analysis integrated with the
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
Bounded asymmetric gaussian mixture-based hidden markov models
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 …
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 …
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 …
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 …
performs better than the classical Gaussian mixture model. In this thesis, we investigate the …
Bayesian inference of hidden markov models using dirichlet mixtures
In this chapter, we propose an efficient unsupervised learning approach following a
Bayesian framework for Hidden Markov Model (HMM) learning. We showcase a unique …
Bayesian framework for Hidden Markov Model (HMM) learning. We showcase a unique …