A hybrid algorithm with GA and DAEM

HongJie Wan; HaoJiang Deng; XueWei Wang

doi:10.1117/12.2011056

14 March 2013 A hybrid algorithm with GA and DAEM

HongJie Wan, HaoJiang Deng, XueWei Wang

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87683D (2013) https://doi.org/10.1117/12.2011056
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

Although the expectation-maximization (EM) algorithm has been widely used for finding maximum likelihood estimation of parameters in probabilistic models, it has the problem of trapping by local maxima. To overcome this problem, the deterministic annealing EM (DAEM) algorithm was once proposed and had achieved better performance than EM algorithm, but it is not very effective at avoiding local maxima. In this paper, a solution is proposed by integrating GA and DAEM into one procedure to further improve the solution quality. The population based search of genetic algorithm will produce different solutions and thus can increase the search space of DAEM. Therefore, the proposed algorithm will reach better solution than just using DAEM. The algorithm retains the property of DAEM and gets the better solution by genetic operation. Experiment results on Gaussian mixture model parameter estimation demonstrate that the proposed algorithm can achieve better performance.

Citation Download Citation

HongJie Wan, HaoJiang Deng, and XueWei Wang "A hybrid algorithm with GA and DAEM", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87683D (14 March 2013); https://doi.org/10.1117/12.2011056

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available