Analog circuit implementation and learning algorithm for nearest neighbor classifiers

Kiichi Urahama, Takeshi Nagao

研究成果: ジャーナルへの寄稿記事

7 引用 (Scopus)

抜粋

Analog electronic circuits are implemented and learning algorithms are presented for Nearest Neighbor (NN) and f-NN. classifiers on the basis of the probabilistic formulation of these classifiers. Electronic networks are compact subthreshold MOS transistor circuits. In the learning algorithm, the place of prototypes and the variance of the probability distribution are optimized by using the steepest descent method for the Kullback-Leibler's information between the network output and the correct membership.

元の言語英語
ページ(範囲)723-730
ページ数8
ジャーナルPattern Recognition Letters
15
発行部数7
DOI
出版物ステータス出版済み - 7 1994

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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