Browsing by Subject "Parameter"
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Item The noise in my head note to self : the only way to tell this story is to tell many(2016-05) Marotta, Gianna Christina; Lynn, Kirk; Dietz, Steven; Engelman, Liz; Carlson, Andrew; Alrutz, MeganThis thesis document discusses my development as a playwright and theater artist over the course of my three years in the MFA Playwriting Program at the University of Texas at Austin. As a framework for inquiry, I will focus primarily on how the practice of making my plays instructions for tuesday, The Caregiving Project, and 381 Bleecker helped me discover the compositional crisis of navigating my own consciousness in the present moment as my writing process. I hope to illuminate how the practice of making these three plays helped me discover writing as an act of increasing my own range of motion—of widening the parameters of the self I allow into my consciousness and my work.Item Parameter estimation in ordinary differential equations(Texas A&M University, 2004-09-30) Ng, Chee LoongThe parameter estimation problem or the inverse problem of ordinary differential equations is prevalent in many process models in chemistry, molecular biology, control system design and many other engineering applications. It concerns the re-construction of auxillary parameters by fitting the solution from the system of ordinary differential equations( from a known mathematical model) to that of measured data obtained from observing the solution trajectory. Some of the traditional techniques (for example, initial value technques, multiple shooting, etc.) used to solve this class of problem have been discussed. A new algorithm, motivated by algorithms proposed by Childs and Osborne(1996) and Z.F.Li's dissertation(2000), has been proposed. The new algorithm inherited the advantages exhibited in the above-mentioned algorithms and, most importantly, the parameters can be transformed to a form that are convenient and suitable for computation. A statistical analysis has also been developed and applied to examples. The statistical analysis yields indications of the tolerance of the estimates and consistency of the observations used.