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dc.contributor.advisorDing, Yanwu
dc.contributor.authorWang, Zuojun
dc.date.accessioned2011-09-02T19:59:42Z
dc.date.available2011-09-02T19:59:42Z
dc.date.copyright2010en
dc.date.issued2010-12
dc.identifier.othert10127
dc.identifier.urihttp://hdl.handle.net/10057/3756
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science.en_US
dc.description.abstractIn this paper, we introduce a novel cycle identification algorithm using Matlab programming to automatically identify cycles in tidal breathing signals. The algorithm is designed in four steps using filtering, derivation, and other signal processing techniques. To verify the effectiveness of the proposed algorithm, its results are compared with those of cycles identified manually by a human coder. Simulations results show that despite the complexity of the respiratory signals, the proposed algorithm can identify cycles more correctly and more efficiently than cycles identified by hand-coding. This algorithm can serve as an important first step toward timely identification and coding of more complex respiratory signals, such as those underlying speech productions.en_US
dc.format.extentix, 28 leaves, ill.en
dc.language.isoen_USen_US
dc.publisherWichita State Universityen_US
dc.rightsCopyright Zuojun Wang, 2010. All rights reserveden
dc.subject.lcshElectronic dissertationsen
dc.titleAutomatic cycle identification in tidal breathing signalsen_US
dc.typeThesisen_US


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