3 resultados para Behavior-Based

em SAPIENTIA - Universidade do Algarve - Portugal


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Dissertação de mest., Natural Language Processing & Human Language Technology, Faculdade de Ciências Humanas e Sociais, Univ. do Algarve, 2011

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All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

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An investigation into the stability of metal insulator semiconductor (MIS) transistors based on alpha-sexithiophene is reported. In particular the kinetics of the threshold voltage shift upon application of a gate bias has been determined. The kinetics follow a stretched-hyperbola type behavior, in agreement with the formalism developed to explain metastability in amorphous-silicon thin film transistors. Using this model, quantification of device stability is possible. Temperature-dependent measurements show that there are two processes involved in the threshold voltage shift, one occurring at T approximate to 220 K and the other at T approximate to 300 K. The latter process is found to be sample dependent. This suggests a relation between device stability and alpha-sexithiophene deposition parameters. Copyright (c) 2005 John Wiley A Sons, Ltd.