Abstract
Two information processing models of the perception of binary patterns are outlined. The H (k-span) model assumes S er;aluates the transitional uncertainty associated with the different k-tuples constituting the pattern. The H (run-span) model assumes S codes the pattern into runs and then evaluates the transitional uncertainty associated with the pattern’s run-tuples. Both models give a measure of the complexity of a pattern. The models are tested by using the complexity measures to predict various response indices of pattern complexity; e.g. judged pattern complexity, mean number of words to describe a pattern, accuracy of recall of a pattern. H (run-span) proved to be highly correlated with all of the pattern complexity indices. H (k-span) received only moderate support.
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This research was supported by grants from the National Institute of Mental Health (MH-11040-0 1 and 13083-01). I am indebted to Thomas C. Todd for his contributions to this research and to James J. Candalino for his assistance in the collection of the data.
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Vitz, P.C. Information, run structure and binary pattern complexity. Perception & Psychophysics 3, 275–280 (1968). https://doi.org/10.3758/BF03212743
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DOI: https://doi.org/10.3758/BF03212743