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dc.contributor.advisor Brady, David en_US
dc.contributor.author Chen, Evan Xuguang en_US
dc.date.accessioned 2015-09-01T19:50:32Z
dc.date.available 2015-12-08T05:30:07Z
dc.date.issued 2015 en_US
dc.identifier.uri http://hdl.handle.net/10161/10452
dc.description Dissertation en_US
dc.description.abstract <p>Conventional mass spectrometry sensing has isomorphic nature, which means measure the input mass spectrum abundance function by a resemble of delta function to avoid ambiguity. However, the delta function nature of traditional mass spectrometry sensing approach imposes trade-offs between mass resolution and throughput/mass analysis time. This dissertation proposes a new field of mass spectrometry sensing which combines both computational signal processing and hardware modification to break the above trade-offs. We introduce the concept of generalized sensing matrix/discretized forward model in mass spectrometry filed. The presence of forward model can bridge the cap between sensing system hardware design and computational sensing algorithm including compressive sensing, feature/variable selection machine learning algorithms, and stat-of-art inversion algorithms. </p><p>Throughout this dissertation, the main theme is the sensing matrix/forward model design subject to the physical constraints of varies types of mass analyzers. For quadrupole ion trap systems, we develop a new compressive and multiplexed mass analysis approach mutli Resonant Frequency Excitation (mRFE) ejection which can reduce mass analysis time by a factor 3-6 without losing mass spectra specificity for chemical classification. A new information-theoretical adaptive sensing and classification framework has proposed on quadrupole mass filter systems, and it can significantly reduces the number of measurements needed and achieve a high level of classification accuracy. Furthermore, we present a coded aperture sector mass spectrometry which can yield a order-of-magnitude throughput gain without compromising mass resolution compare to conventional single slit sector mass spectrometer.</p> en_US
dc.subject Electrical engineering en_US
dc.subject Computational mass spectrometry en_US
dc.subject Computational sensing en_US
dc.subject magnetic sector spectrometer en_US
dc.subject Mass spectrometry en_US
dc.subject Quadrupole ion trap en_US
dc.subject Quadrupole mass filter en_US
dc.title Computational Mass Spectrometry en_US
dc.type Dissertation en_US
dc.department Electrical and Computer Engineering en_US
duke.embargo.months 3 en_US

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