Show simple item record

dc.contributor.authorSaatçı, Esra
dc.contributor.authorAkan, Aydın
dc.date.accessioned2016-05-11T12:46:21Z
dc.date.available2016-05-11T12:46:21Z
dc.date.issued2010-02
dc.identifier.issn0165-1684
dc.identifier.urihttp://hdl.handle.net/11413/1316
dc.description.abstractModeling of respiratory system under non-invasive ventilation by using measured respiratory signals is of great interest in respiratory mechanics research area. Statistical processing techniques in the time-domain may be utilized as an alternative to the commonly used frequency-domain analysis to estimate model parameters. In this work, we propose using a generalized Gaussian distribution (GGD) to model the measurement noise in the respiratory system identification problem. The parameters of the GGD (i.e. the mean, the variance and the shape) are estimated by maximum likelihood (ML) and moment based estimators. However, the estimation error should also be taken into account which is in fact investigated as measurement innovations together with the measurement noise. Thus the Kalman iterations are applied with the help of the score function to compute the measurement innovations. Finally, the complete picture of the measurement noise and innovation analysis of the respiratory models is obtained which helped us to evaluate the non-Gaussian noise extension in the respiratory system analysis. (C) 2009 Elsevier B.V. All rights reserved.tr_TR
dc.language.isoen_UStr_TR
dc.publisherElsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlandstr_TR
dc.relationSignal Processingtr_TR
dc.subjectGeneralized Gaussian distributiontr_TR
dc.subjectMaximum likelihood estimationtr_TR
dc.subjectBiomedical signal processingtr_TR
dc.subjectRespiratory modelstr_TR
dc.subjectmechanicstr_TR
dc.subjectlungtr_TR
dc.subjectGenelleştirilmiş Gauss dağılımıtr_TR
dc.subjectEnçok olabilirlik kestirimitr_TR
dc.subjectBiyomedikal sinyal işlemetr_TR
dc.subjectsolunum modellertr_TR
dc.subjectmekaniktr_TR
dc.subjectakciğertr_TR
dc.titleRespiratory Parameter Estimation In Non-İnvasive Ventilation Based On Generalized Gaussian Noise Modelstr_TR
dc.typeArticletr_TR
dc.contributor.authorIDTR112197tr_TR
dc.contributor.authorIDTR2918tr_TR
dc.identifier.wos000271332100007
dc.identifier.wos271332100007en


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record