Chapter

Models for Far-Apart Values

Norma van Surdam Graham

in Visual Pattern Analyzers

Published in print December 1989 | ISBN: 9780195051544
Published online January 2008 | e-ISBN: 9780199872183 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195051544.003.0004

Series: Oxford Psychology Series

 Models for Far-Apart Values

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Summation experiments using patterns that are far apart along any dimension (e.g., two lines of very different orientations) can answer the question of whether there are multiple analyzers along that dimension. Two classes of models are presented: probabilistic models in which variability in analyzers' outputs causes increased performance (probability summation); and deterministic models that predict increased performance without assuming variability by incorporating nonlinear pooling (Minkowski, Quick) into decision rules. This chapter presents the results on the spatial-frequency dimension (and their possible dependence on retinal inhomogeneity). An appendix derives convenient formulas in terms of observable quantities to allow easy use of the models in many situations. This chapter together with Chapters 7 through 10 cover what is sometimes called multidimensional signal detection theory.

Keywords: summation experiments; quick pooling; Minkowski; multidimensional signal detection theory; decision rules; variability; probability summation; spatial frequency; retinal inhomogeneity

Chapter.  20163 words.  Illustrated.

Subjects: Neuropsychology

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