UPM Institutional Repository

The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM)


Citation

Mohd Yusoff, Mohd Izhan and Abu Bakar, Mohd. Rizam and Mohd Nor, Abu Hassan Shaari (2009) The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM). Pertanika Journal of Science & Technology, 17 (2). 231 - 243. ISSN 0128-7680

Abstract

Expectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. In this paper, the performance of the said algorithm in finding the Maximum Likelihood for the Gaussian Mixed Models (GMM), a probabilistic model normally used in fraud detection and recognizing a person’s voice in speech recognition field, is shown and discussed. At the end of the paper, some suggestions for future research works will also be given.


Download File

[img]
Preview
PDF (Abstract)
The performance of expectation maximization.pdf

Download (175kB) | Preview
Official URL or Download Paper: http://pertanika.upm.edu.my/Pertanika

Additional Metadata

Item Type: Article
Subject: Expectation-maximization algorithms.
Subject: Gaussian processes.
Subject: Estimation theory.
Divisions: Faculty of Science
Publisher: Universiti Putra Malaysia Press
Keywords: Expectation Maximization (EM), Gaussian Mixed Models (GMM), Box and Muller Transformation
Depositing User: Najwani Amir Sariffudin
Date Deposited: 25 Jun 2012 08:36
Last Modified: 23 Oct 2015 02:51
URI: http://psasir.upm.edu.my/id/eprint/17261
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item