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Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem
Joint Authors
Zhu, Lingyan
Jiang, Shanshan
Wang, Yaming
Zhang, Heng
Huang, Wenqing
Jiang, Mingfeng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-25
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs) from body surface potentials (BSPs).
In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials) and multi-outputs (transmembrane potentials), which can be solved by the support vector regression (SVR) method.
In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully.
Three different optimization methods, that is, genetic algorithm (GA), differential evolution (DE) algorithm, and particle swarm optimization (PSO), are proposed to determine optimal hyperparameters of the SVR model.
In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided.
The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem.
Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs.
American Psychological Association (APA)
Jiang, Mingfeng& Jiang, Shanshan& Zhu, Lingyan& Wang, Yaming& Huang, Wenqing& Zhang, Heng. 2013. Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-450438
Modern Language Association (MLA)
Jiang, Mingfeng…[et al.]. Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-450438
American Medical Association (AMA)
Jiang, Mingfeng& Jiang, Shanshan& Zhu, Lingyan& Wang, Yaming& Huang, Wenqing& Zhang, Heng. Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-450438
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-450438