Undergraduate student of Science and Technology and Computer Science at the Federal University of ABC. Currently, the student has an undergraduation research scholarship granted by the São Paulo Research Foundation (FAPESP). (Source: Lattes Curriculum)
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Artificial Neural Networks (ANN) have reached noticeable performance in many applications. In the context of supervised learning, network training is done traditionally using the backpropagation algorithm. However, this algorithm has some limitations, among which stand out its high convergence rate to local solutions and the disadvantage of assuming a fixed topology for an ANN. In this co…
Errors in digital data are a common issue faced by computational systems when dealing with tasks such as transmission and storage of information. Recently, in certain contexts, such as approximate computing, a considerably high level of errors might be tolerated in order to achieve lower power consumption. In these cases, an error control method is required. An option is the error control…
The Blind Source Separation problem is a model that can be applied to solve several real-world problems that are modeled as a mixture of independent components. Unlike its linear case, a general solution framework for the Nonlinear Blind Source Separation (NLBSS) problem has not been achieved yet. Some approaches based on constrained models have been proposed so far, however, the success…
| 2 / 2 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
| 3 / 3 | All Scholarships |
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