Batch-Learning Self-Organizing Map with False-Neighbor Degree Between Neurons

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Haruna Matsushita and Yoshifumi Nishio",
  title =        "Batch-Learning Self-Organizing Map with False-Neighbor
                 Degree Between Neurons",
  booktitle =    "2008 IEEE World Congress on Computational
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "2259--2266",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1821-3",
  file =         "NN0660.pdf",
  DOI =          "doi:10.1109/IJCNN.2008.4634110",
  abstract =     "This study proposes a Batch-Learning Self- Organising
                 Map with False-Neighbor degree between neurons (called
                 BL-FNSOM). False-Neighbor degrees are allocated between
                 adjacent rows and adjacent columns of BL-FNSOM. The
                 initial values of all of the false-neighbor degrees are
                 set to zero, however, they are increased with learning,
                 and the false neighbour degrees act as a burden of the
                 distance between map nodes when the weight vectors of
                 neurons are updated. BLFNSOM changes the neighbourhood
                 relationship more flexibly according to the situation
                 and the shape of data although using batch learning. We
                 apply BL-FNSOM to some input data and confirm that
                 FN-SOM can obtain a more effective map reflecting the
                 distribution state of input data than the conventional
                 Batch-Learning SOM.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",

Genetic Programming entries for Haruna Matsushita Yoshifumi Nishio