Antônio de Pádua Braga
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Redes neurais artificiais: teoria e aplicações
AP Braga, A Carvalho, TB Ludermir
Livros Técnicos e Científicos, 2000
Novel cost-sensitive approach to improve the multilayer perceptron performance on imbalanced data
CL Castro, AP Braga
IEEE transactions on neural networks and learning systems 24 (6), 888-899, 2013
Learning from imbalanced data sets with weighted cross-entropy function
YS Aurelio, GM De Almeida, CL de Castro, AP Braga
Neural processing letters 50, 1937-1949, 2019
SVM-KM: speeding SVMs learning with a priori cluster selection and k-means
MB De Almeida, A de Pádua Braga, JP Braga
Proceedings. Vol. 1. Sixth Brazilian Symposium on Neural Networks, 162-167, 2000
Improving generalization of MLPs with multi-objective optimization
R de Albuquerque Teixeira, AP Braga, RHC Takahashi, RR Saldanha
Neurocomputing 35 (1-4), 189-194, 2000
Weightless neural models: a review of current and past works
TB Ludermir, ACPLF Carvalho, AP Braga, MCP De Souto
Neural Computing Surveys 2, 41-61, 1999
Intelligent thermographic diagnostic applied to surge arresters: a new approach
CAL Almeida, AP Braga, S Nascimento, V Paiva, HJA Martins, R Torres, ...
IEEE Transactions on power delivery 24 (2), 751-757, 2009
Sliding mode algorithm for training multilayer artificial neural networks
GG Parma, BR Menezes, AP Braga
Electronics Letters 34 (1), 97-98, 1998
Redes neurais artificiais
AP Braga, A Carvalho, TB Ludermir
Teoria e Aplicaçoes, 2000
Improving generalization of MLPs with sliding mode control and the Levenberg–Marquardt algorithm
MA Costa, A de Pádua Braga, BR de Menezes
Neurocomputing 70 (7-9), 1342-1347, 2007
Evaluating five different adaptive decomposition methods for EEG signal seizure detection and classification
VR Carvalho, MFD Moraes, AP Braga, EMAM Mendes
Biomedical Signal Processing and Control 62, 102073, 2020
Black and gray-box identification of a hydraulic pumping system
BHG Barbosa, LA Aguirre, CB Martinez, AP Braga
IEEE Transactions on control systems technology 19 (2), 398-406, 2010
An efficient multi-objective learning algorithm for RBF neural network
I Kokshenev, AP Braga
Neurocomputing 73 (16-18), 2799-2808, 2010
Training neural networks with a multi-objective sliding mode control algorithm
MA Costa, AP Braga, BR Menezes, RA Teixeira, GG Parma
Neurocomputing 51, 467-473, 2003
Prediction and simulation errors in parameter estimation for nonlinear systems
LA Aguirre, BHG Barbosa, AP Braga
Mechanical Systems and Signal Processing 24 (8), 2855-2867, 2010
Sliding mode neural network control of an induction motor drive
GG Parma, BR Menezes, AP Braga, MA Costa
International Journal of Adaptive Control and Signal Processing 17 (6), 501-508, 2003
Artificial neural networks: theory and applications
AP Braga, APL Carvalho, TB Ludermir
LTC Editora, Rio de Janeiro,, 2000
Reinforcement learning of a simple control task using the spike response model
MS de Queiroz, RC de Berrêdo, A de Pádua Braga
Neurocomputing 70 (1-3), 14-20, 2006
Evolutionary radial basis functions for credit assessment
E Lacerda, AC Carvalho, AP Braga, TB Ludermir
Applied Intelligence 22, 167-181, 2005
A multi-objective approach to RBF network learning
I Kokshenev, AP Braga
Neurocomputing 71 (7-9), 1203-1209, 2008
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