22 resultados para Z-domain precoding
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Dissertação para obtenção do Grau de Doutor em Sistemas de Bioengenharia
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Dissertação de Mestrado em Engenharia Informática
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Electronics Letters Vol.38, nº 19
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Dissertação apresentada no Departamento de Física na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Biomédica
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Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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PLOS ONE, 4(8):ARTe6820
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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pp. 219-230
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J. Am. Chem. Soc., 2003, 125 (51), pp 15708–15709 DOI: 10.1021/ja038344n
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Dissertação submetida para a obtenção do grau de Doutor em Engenharia Electrotécnica e de Computadores
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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Línguas, Literaturas e Culturas
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Revista do IHA, N.3 (2007), pp.238-253
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This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.