Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351850 | Computers in Biology and Medicine | 2005 | 17 Pages |
Abstract
The classification problem of respiratory sound signals has been addressed by taking into account their cyclic nature, and a novel hierarchical decision fusion scheme based on the cooperation of classifiers has been developed. Respiratory signals from three different classes are partitioned into segments, which are later joined to form six different phases of the respiration cycle. Multilayer perceptron classifiers classify the parameterized segments from each phase and decision vectors obtained from different phases are combined using a nonlinear decision combination function to form a final decision on each subject. Furthermore a new regularization scheme is applied to the data to stabilize training and consultation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Emin Ãaǧatay Güler, Bülent Sankur, Yasemin P. Kahya, Sarunas Raudys,