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Classification image weights and internal noise level estimationFor the linear discrimination of two stimuli in white Gaussian noise in the presence of internal noise, a method is described for estimating linear classification weights from the sum of noise images segregated by stimulus and response. The recommended method for combining the two response images for the same stimulus is to difference the average images. Weights are derived for combining images over stimuli and observers. Methods for estimating the level of internal noise are described with emphasis on the case of repeated presentations of the same noise sample. Simple tests for particular hypotheses about the weights are shown based on observer agreement with a noiseless version of the hypothesis.
Document ID
20040087756
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Ahumada, Albert J Jr
(NASA Ames Research Center Moffett Field CA United States)
Date Acquired
August 21, 2013
Publication Date
January 1, 2002
Publication Information
Publication: Journal of vision (Charlottesville, Va.)
Volume: 2
Issue: 1
Subject Category
Life Sciences (General)
Distribution Limits
Public
Copyright
Other

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