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Roelof K. Brouwer: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Roelof K. Brouwer
    Storing many-to-many mappings on a feed-forward neural network using fuzzy sets. [Citation Graph (0, 0)][DBLP]
    ESANN, 2002, pp:13-18 [Conf]
  2. Roelof K. Brouwer
    An integer recurrent artificial neural network for classifying feature vectors. [Citation Graph (0, 0)][DBLP]
    ESANN, 1999, pp:307-312 [Conf]
  3. Roelof K. Brouwer, Witold Pedrycz
    One-to-many mappings represented on feed-forward networks. [Citation Graph (0, 0)][DBLP]
    ESANN, 2001, pp:365-370 [Conf]
  4. Roelof K. Brouwer
    Using a Helper FFN to Represent the Cost Function for Training DRNN's by Gradient Descent. [Citation Graph (0, 0)][DBLP]
    HIS, 2002, pp:707-714 [Conf]
  5. Roelof K. Brouwer, Witold Pedrycz
    A Feed Forward Network and Its Training Algorithm for Producing Sets. [Citation Graph (0, 0)][DBLP]
    Neural Networks and Computational Intelligence, 2003, pp:112-117 [Conf]
  6. Roelof K. Brouwer
    A Fuzzy Threshold Max-Product Unit, with Learning Algorithm, for Classification of Pattern Vectors. [Citation Graph (0, 0)][DBLP]
    SBRN, 2000, pp:208-212 [Conf]
  7. Roelof K. Brouwer, Witold Pedrycz
    Training a feed-forward network with incomplete data due to missing input variables. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2003, v:3, n:1, pp:23-36 [Journal]
  8. Roelof K. Brouwer
    Fuzzy set covering of a set of ordinal attributes without parameter sharing. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2006, v:157, n:13, pp:1775-1786 [Journal]
  9. Roelof K. Brouwer
    A hybrid neural network for input that is both categorical and quantitative. [Citation Graph (0, 0)][DBLP]
    Int. J. Intell. Syst., 2004, v:19, n:10, pp:979-1001 [Journal]
  10. Roelof K. Brouwer
    The Backpropagation Algorithm in J, a Fast Prototyping Tool for Researching Neural Networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:4, pp:273-284 [Journal]
  11. Roelof K. Brouwer
    Growing of a Fuzzy Recurrent Artificial Neural Network (Frann) for Pattern Classification. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:4, pp:335-350 [Journal]
  12. Roelof K. Brouwer
    A Discrete Fully Recurrent Network of Max Product Units for Associative Memory and Classification. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2002, v:12, n:3-4, pp:247-262 [Journal]
  13. Roelof K. Brouwer
    A Proposed Max-Product Threshold Unit for Classification of Pattern Vectors. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2001, v:11, n:3, pp:271-279 [Journal]
  14. Roelof K. Brouwer
    Feed-forward neural network for one-to-many mappings using fuzzy sets. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:57, n:, pp:345-360 [Journal]
  15. Roelof K. Brouwer
    Training a feed-forward network by feeding gradients forward rather than by back-propagation of errors. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1997, v:16, n:2, pp:117-126 [Journal]
  16. Roelof K. Brouwer
    An Integer Recurrent Artificial Neural Network for Classifying Feature Vectors. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 2000, v:14, n:3, pp:339-355 [Journal]
  17. Roelof K. Brouwer
    A Discrete Fully Recurrent Network of Sigmoid Units for Associative Memory and Pattern Classification. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 2002, v:16, n:5, pp:527-550 [Journal]
  18. Roelof K. Brouwer
    A Fuzzy Recurrent Artificial Neural Network (FRANN) for Pattern Classification. [Citation Graph (0, 0)][DBLP]
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2000, v:8, n:5, pp:525-538 [Journal]
  19. Roelof K. Brouwer
    A Solution Method for Truncated Normalized Max Product Fuzzy Set of Equations. [Citation Graph (0, 0)][DBLP]
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2003, v:11, n:3, pp:361-372 [Journal]
  20. Roelof K. Brouwer
    Fuzzy Rule Extraction from a Feed Forward Neural Network by Training a Representative Fuzzy Neural Network Using Gradient Descent. [Citation Graph (0, 0)][DBLP]
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2005, v:13, n:6, pp:673-698 [Journal]
  21. Roelof K. Brouwer
    A feed-forward network for input that is both categorical and quantitative. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:7, pp:881-890 [Journal]
  22. Roelof K. Brouwer
    A method for training recurrent neural networks for classification by building basins of attraction. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1995, v:8, n:4, pp:597-603 [Journal]
  23. Roelof K. Brouwer
    Automatic Growing of a Hopfield Style Network During Training for Classification. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:3, pp:529-537 [Journal]
  24. Roelof K. Brouwer
    Implementation of the Exclusive-Or Function in a Hopfield Style Recurrent Network. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1997, v:5, n:1, pp:1-7 [Journal]
  25. Roelof K. Brouwer
    A Fuzzy Neuron with Binary Input and its Training Algorithm. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1999, v:9, n:1, pp:25-33 [Journal]
  26. Roelof K. Brouwer
    Training of a discrete recurrent neural network for sequence classification by using a helper FNN. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2005, v:9, n:10, pp:749-756 [Journal]
  27. Roelof K. Brouwer
    Automatic training of a min-max neural network for function approximation by using a second feed forward network. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2005, v:9, n:5, pp:393-397 [Journal]
  28. Roelof K. Brouwer, Witold Pedrycz
    Set oriented mappings on neural networks. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2003, v:8, n:1, pp:28-37 [Journal]
  29. Mahnhoon Lee, Roelof K. Brouwer
    Fuzzy Clustering and Mapping of Ordinal Values to Numerical. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:538-543 [Conf]
  30. Mahnhoon Lee, Roelof K. Brouwer
    Likelihood Based Fuzzy Clustering for Data Sets of Mixed Features. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:544-549 [Conf]

  31. A Method of Proximity Matrix Based Fuzzy Clustering. [Citation Graph (, )][DBLP]


  32. A New Method of Fuzzy Clustering of Ordinal Feature Valued Vectors. [Citation Graph (, )][DBLP]


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