ISSN:
1432-0770
Source:
Springer Online Journal Archives 1860-2000
Topics:
Biology
,
Computer Science
,
Physics
Notes:
Abstract Behavioral experiments are indispensable for the analysis of biological systems for cognition and recognition. When these are carried out as detection experiments three types of description can be used for the problem of visual pattern recognition which allow conclusions to be drawn on the operating function of the system. Provided that the signals to be recognized have additive noise superimposed on them, system description is possible: 1. on the basis on the probabilities of recognition and of mix-up,—2. through the analysis of the transformation of distribution densities of the noise,—3. by means of the measurable distances of the patterns from each other in feature space.-The analysis of the distribution densities shows that the human visual system acts like a linear classifier in the classification of six geometrical patterns. The independence of the classification from intensity as well as the human reaction to alteration in the power spectrum of the noise support this result. Simulation experiments on a computer show the efficacy of various biological relevant parameters for the linear classification and suggest that a narrow band and probably feature specific filtering precedes the classification.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00365209
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