Pedro De Miguel

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The study of Artificial Neural Networks (ANN) has been fascinating over the years and its development has strongly grown in recent years. The neural networks methods have become to be increasingly convincing for solving complex problems, through artificial intelligence. In particular, this work, focused on the development of an artificial neural network for(More)
ii Para ela. Onde quer que esteja. iii iv Acknowledgments F IRST of all, I would like to appreciate all the dedication, knowledge and support given to me by my supervisor Pere Gilabert, from the moment in which we first discussed this thesis up until the moment I presented it. I would also like to address my gratefulness to other people with whom I shared(More)
Traditional small-scale vibration energy harvesters have typically low efficiency of energy harvesting from low frequency vibrations. Several recent studies have indicated that introduction of nonlinearity can significantly improve the efficiency of such systems. Motivated by these observations we have studied the nonlinear electrostatic energy harvester(More)
i Dedicated to my parents Raimundo and Rosalda, my wife Ana and my son Pedro Miguel ii iii Acknowledgements This is one of the best moments in my doctoral program-to publicly acknowledge those who have contributed, in many different ways, to make my success a part of their own. I am most fortunate to have had Prof. Dr. Orlando Belo as my supervisor. I wish(More)
professor of the Owen Graduate School of Management, for his invaluable advice while writing my thesis and my parents whose support has been invaluable. In addition, I am indebted to all the people in the Management of Technology program in particular to Mary Jane Buchanan and Flo Fottrell, thank you for all your help.
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