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A Study on Unsupervised Learning Method of RAM-based Neural Net

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2011, 16(1), pp.31-38
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

박상무 1 Seongjin Kim 2 이동형 3 LEE SOO DONG 4 ChoelYoung Ock 2

1영산대학교
2울산대학교
3한국폴리텍VII대학 울산캠퍼스
4울산과학대학교

Accredited

ABSTRACT

A RAM-based Neural Net is a weightless neural network based on binary neural network. 3-D neural network using this paper is binary neural network with multiful information bits and store counts of training. Recognition method by MRD technique is based on the supervised learning. Therefore neural network by itself can not distinguish between the categories and well-separated categories of training data can achieve only through the performance. In this paper, unsupervised learning algorithm is proposed which is trained existing 3-D neural network without distinction of data, to distinguish between categories depending on the only input training patterns. The training data for proposed unsupervised learning provided by the NIST handwritten digits of MNIST which is consist of 0 to 9 multi-pattern, a randomly materials are used as training patterns. Through experiments, neural network is to determine the number of discriminator which each have an idea of the handwritten digits that can be interpreted.

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