Information, run structure and binary pattern complexity

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. © 1968 Psychonomic Society, Inc.