{"id":{"repo_id":"trento","oai_identifier":"oai:iris.unitn.it:11572/368063"},"canonical_url":"https://search.dev.ndltd.org/etd/trento/oai:iris.unitn.it:11572/368063","repository":{"repo_id":"trento","name":"Università degli Studi di Trento","base_url":"https://iris.unitn.it/oai/request"},"display":{"title":"SVM-based Strategies as applied to Electromagnetics","abstract":"In the framework of the electromagnetic approaches based on learning-by-example (LBE) techniques, this thesis focuses on the development of a strategy for the solution of complex problems by means of support vector machine (SVM). The proposed instance-based classification method compared to more traditional optimization techniques solves the arising quadratic optimization problem with constraints in a simple and reliable way leveraging on the statistical learning theory which enables the design of optimal classifiers with a solid theoretical framework. A set of input/output relations representing the training dataset permits to avoid the a-priori knowledge about the system. By exploiting the generalization capabilities, the robustness against noise and the real-time performance, this technique has been proven to be suitable for more than one real-world application. The investigated problems are addressed by integrating the measured electromagnetic field with a suitably defined classifier that is aimed at defining a real-time reconstruction of the observed domain. For each application field a set of numerical results have been reported in order to assess the effectiveness and flexibility of the proposed approach. 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By exploiting the generalization capabilities, the robustness against noise and the real-time performance, this technique has been proven to be suitable for more than one real-world application. The investigated problems are addressed by integrating the measured electromagnetic field with a suitably defined classifier that is aimed at defining a real-time reconstruction of the observed domain. For each application field a set of numerical results have been reported in order to assess the effectiveness and flexibility of the proposed approach. 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For each application field a set of numerical results have been reported in order to assess the effectiveness and flexibility of the proposed approach. The real-time capabilities as well as the feasibility when dealing with real data have been also verified by means of an experimental setup for the passive tracking of non-cooperative targets moving throughout the investigated area."]},{"key":"dc:title","label":"Title","values":["SVM-based Strategies as applied to Electromagnetics"]}]}],"canonical_facts":{"dc:contributor":["Viani, Federico","Massa, Andrea"],"dc:creator":["Viani, Federico"],"dc:date":["2010"],"dc:description":["In the framework of the electromagnetic approaches based on learning-by-example (LBE) techniques, this thesis focuses on the development of a strategy for the solution of complex problems by means of support vector machine (SVM). 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