PMID: 7334285Jan 1, 1981Paper

Analysis of pattern recognition by man using detection experiments

Journal of Mathematical Biology
B Türke

Abstract

This paper addresses the problem of analyzing biological pattern recognition systems. As no complete analysis is possible due to limited observability, the theoretical part of the paper examines some principles of construction for recognition systems. The relations between measurable and characteristic variables of these systems are described. The results of the study are: 1. Human recognition systems can always be described by a model consisting of an analyzer (FA) and a linear classifier. 2. The linearity of the classifier places no limits on the universal validity of the model. The principle of organization of such a system may be put into effect in many different ways. 3. The analyzer function FA determines the transformation of external patterns into their internal representations. For the experiments described in this paper, FA can be approximated by a filtering operation and a transformation of features (contour line filter). 4. Narrow band filtering (comb filter) in the space frequency domain is inadequate for pattern recognition because noise of different bandwidths and mean frequencies affects sinusoidal gratings differently. This excludes the use of a Fourier analyzer. 5. The relations between the measurable variable...Continue Reading

References

Jun 21, 1978·Biological cybernetics·G Bohn
Feb 7, 1977·Biological cybernetics·M Fansa, W von Seelen

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