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dc.contributor.authorWang, Kunpeng
dc.date.accessioned2015-12-17T19:34:59Z
dc.date.available2015-12-17T19:34:59Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10222/64728
dc.description.abstractEntropy is a well-known quantity that is used to describe verious phenomena in physics and information theory. Like energy or information, entropy cannot be measured directly and traditionally is used to describe the state of other physical quantities. Recently, a Russian physicist Anatoly Panchenkov introduced a new, more general, notion of entropy. In view of the principle of maximum P-entropy, a system evolves in the direction of its maximum lifespan , e.g., the life expectancy of humans, or business structures increases. An important feature of the differential equations that follow from the principle of maximum P-entropy is that they can be used to describe not only evolution, for example, as the equation of classical mechanics, but also events. In this thesis we will investigate how to employ the P-entropy to construct mathematical models that can be used in the theory of monitoring.en_US
dc.language.isoenen_US
dc.subjectMath modellingen_US
dc.subjectEntropyen_US
dc.subjectHamiltonian systemen_US
dc.titleEntropy and the Monitoring Problemen_US
dc.typeThesis
dc.date.defence2015-12-14
dc.contributor.departmentDepartment of Mathematics & Statistics - Math Divisionen_US
dc.contributor.degreeMaster of Scienceen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorDavid Ironen_US
dc.contributor.thesis-readerRobert Milsonen_US
dc.contributor.thesis-readerChelluri C.A. Sastrien_US
dc.contributor.thesis-supervisorRoman Smirnoven_US
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