Context propagation based on membership feedback

Kohei Inoue, Kiichi Urahama

Research output: Contribution to journalArticlepeer-review


The authors discuss a simple model for pattern discrimination incorporating temporal or spatial context by feedback of the membership values output at the high-rank winner-take-all (WTA) neurons to the lower-rank pattern selection response neurons. They propose a teacherless training method based on maximum likelihood. First, for the temporal context, they study examples with the feedback of discrimination effect of a first moment to the next moment, and demonstrate that clustering is performed by proximity of presentation moments rather than by the pattern similarity. Next, for the spatial context, they show that a similar pattern recognition method can be applied to spatial smoothing of image patterns.

Original languageEnglish
Pages (from-to)45-52
Number of pages8
JournalSystems and Computers in Japan
Issue number1
Publication statusPublished - Jan 2001

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics


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