Analog circuit implementation and learning algorithm for nearest neighbor classifiers

Kiichi Urahama, Takeshi Nagao

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)723-730
    Number of pages8
    JournalPattern Recognition Letters
    Volume15
    Issue number7
    DOIs
    Publication statusPublished - Jul 1994

    All Science Journal Classification (ASJC) codes

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

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