Nonvectorial kmer and topology preservation

نویسندگان

  • Susana Vegas-Azcárate
  • Temujin Gautama
  • Marc M. Van Hulle
چکیده

In nonvectorial topographic maps the data sequences are not previously converted into histogram vectors, thus avoiding the shortcomings associated to these representations. Like in standard vectorial topographic maps, in nonvectorial learning algorithms the optimal speed of shrinking of the neighbourhood range should be experimentally determined. This paper shows how UDL monitoring scheme can be extended to the case of the kernel-based Maximum Entropy Learning Rule (kMER).

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تاریخ انتشار 2006