J
João Pedro Neto
Researcher at University of Lisbon
Publications - 25
Citations - 132
João Pedro Neto is an academic researcher from University of Lisbon. The author has contributed to research in topics: Artificial neural network & Combinatorial game theory. The author has an hindex of 5, co-authored 23 publications receiving 110 citations. Previous affiliations of João Pedro Neto include University of Évora & Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa.
Papers
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Journal ArticleDOI
Symbolic processing in neural networks
TL;DR: It is shown how to use resource bounds to speed up computations over neural nets, through suitable data type coding like in the usual programming languages.
Journal ArticleDOI
Guaranteed Scoring Games
TL;DR: It is proved that if a game has an inverse it is obtained by `switching the players' and the structure of GS is a quotient monoid with partially ordered congruence classes.
Book ChapterDOI
Turing Universality of Neural Nets (Revisited)
TL;DR: It is shown how to use recursive function theory to prove Turing universality of finite analog recurrent neural nets, with a piecewise linear sigmoid function as activation function.
Journal ArticleDOI
Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control.
Konstantinos Nizamis,Noortje H.M. Rijken,Robbert van Middelaar,João Pedro Neto,Bart F.J.M. Koopman,Massimo Sartori +5 more
TL;DR: The ability of the DMD participants to produce repeatable HD-sEMG patterns was unexpectedly comparable to that of healthy participants, and the same holds true for their offline myocontrol performance, disproving the hypothesis and suggesting a clear potential for the myOControl of wearable exoskeletons.
Posted Content
Guaranteed Scoring Games
TL;DR: In this paper, the authors present the structure of Guaranteed Scoring Games (GS) and the techniques needed to analyze a sum of guaranteed games and demonstrate how to compare the games via a finite algorithm instead, extending ideas of Ettinger and also Siegel.