50 resultados para STRUCTURAL BRAIN ABNORMALITIES


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Dissertação para a obtenção de grau de doutor em Bioquímica pelo Instituto de Tecnologia Química e Biológica. Universidade Nova de Lisboa

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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).

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Dissertação para obtenção do Grau de Mestre em Bioquímica Estrutural e Funcional

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Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade N ova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical Engineering

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Dissertation presented to obtain the Ph.D degree in Biology

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Dissertation to obtain a Master Degree in Molecular Genetics and Biomedicine at Faculty of Sciences and Technology,Universidade Nova de Lisboa

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A thesis to obtain a Master degree in Structural and Functional Biochemistry

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Dissertação para obtenção do Grau de Doutor em Sistemas de Bioengenharia

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Fundação para a Ciência e a Tecnologia - SFRH/BD/42848/2008, através do Programa MIT_Portugal em Sistemas de Bioengenharia; projectos PTDC/SAUNEU/104415/2008 e Projecto ref. 96542 da Fundação Caloust Gulbenkian

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The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience