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Guilherme De A. Barreto: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Nonlinear Modeling of Dynamic Systems with the Self-Organizing Map. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:975-980 [Conf]
  2. Guilherme De A. Barreto, João Cesar M. Mota, Luís Gustavo M. Souza, Rewbenio A. Frota, L. Aguayo, J. S. Yamamoto, Pedro Eduardo de Oliveira Macedo
    Competitive Neural Networks for Fault Detection and Diagnosis in 3G Cellular Systems. [Citation Graph (0, 0)][DBLP]
    ICT, 2004, pp:207-213 [Conf]
  3. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Predictive Modeling and Planning of Robot Trajectories Using the Self-Organizing Map. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 2004, pp:1156-1165 [Conf]
  4. Guilherme De A. Barreto, João Cesar M. Mota, Luís Gustavo M. Souza, Rewbenio A. Frota
    Nonstationary Time Series Prediction Using Local Models Based on Competitive Neural Networks. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 2004, pp:1146-1155 [Conf]
  5. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:207-212 [Conf]
  6. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Competitive and Temporal Hebbian Learning for Production of Robot Trajectories. [Citation Graph (0, 0)][DBLP]
    SBRN, 1998, pp:96-101 [Conf]
  7. Antonio C. Padoan Jr., Aluizio F. R. Araújo, Guilherme De A. Barreto
    Dynamic Modeling of Robotic Trajectories Using the Parametrized SOM. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:195- [Conf]
  8. Aluizio F. R. Araújo, Guilherme De A. Barreto
    A Self-Organizing Context-Based Approach to the Tracking of Multiple Robot Trajectories. [Citation Graph (0, 0)][DBLP]
    Appl. Intell., 2002, v:17, n:1, pp:101-119 [Journal]
  9. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Unsupervised Learning and Temporal Context to Recall Complex Robot Trajectories. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2001, v:11, n:1, pp:11-22 [Journal]
  10. Guilherme De A. Barreto, Aluizio F. R. Araújo
    Unsupervised Learning and Recall of Temporal Sequences: An Application to Robotics. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:3, pp:235-242 [Journal]
  11. Antonio C. Padoan Jr., Guilherme De A. Barreto, Aluizio F. R. Araújo
    Modeling and Production of Robot Trajectories Using the Temporal Parametrized Self Organizing Maps. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2003, v:13, n:2, pp:119-127 [Journal]
  12. Guilherme De A. Barreto, Aluizio F. R. Araújo, Stefan C. Kremer
    A Taxonomy for Spatiotemporal Connectionist Networks Revisited: The Unsupervised Case. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2003, v:15, n:6, pp:1255-1320 [Journal]
  13. Guilherme De A. Barreto, Luís Gustavo M. Souza
    Adaptive filtering with the self-organizing map: A performance comparison. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:6-7, pp:785-798 [Journal]
  14. Guilherme De A. Barreto, Aluizio F. R. Araújo, C. Dücker, Helge Ritter
    A distributed robotic control system based on a temporal self-organizing neural network. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part C, 2002, v:32, n:4, pp:347-357 [Journal]
  15. Cláudio M. S. Medeiros, Guilherme A. Barreto
    An Efficient Method for Pruning the Multilayer Perceptron Based on the Correlation of Errors. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:219-228 [Conf]

  16. On Self-Organizing Feature Map (SOFM) Formation by Direct Optimization Through a Genetic Algorithm. [Citation Graph (, )][DBLP]


  17. Directly Optimizing Topology-Preserving Maps with Evolutionary Algorithms. [Citation Graph (, )][DBLP]


  18. Novelty Detection in Time Series Through Self-Organizing Networks: An Empirical Evaluation of Two Different Paradigms. [Citation Graph (, )][DBLP]


  19. A New Look at Nonlinear Time Series Prediction with NARX Recurrent Neural Network. [Citation Graph (, )][DBLP]


  20. Time Series Clustering for Anomaly Detection Using Competitive Neural Networks. [Citation Graph (, )][DBLP]


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