December 2007
Volume 7, Issue 15
Free
OSA Fall Vision Meeting Abstract  |   December 2007
Problems with modeling detection and identification of signals in noise
Author Affiliations
  • Stanley Klein
    Optometry
  • Dennis Levi
    UC Berkeley, School of Optometry
Journal of Vision December 2007, Vol.7, 73. doi:10.1167/7.15.73
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Stanley Klein, Dennis Levi; Problems with modeling detection and identification of signals in noise. Journal of Vision 2007;7(15):73. doi: 10.1167/7.15.73.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

A powerful method for peeking into the black box of perception is to measure thresholds for detecting and identifying patterns in noise. A typical experiment varies two parameters: the rms strength of the external noise (Next) and the criterion at which threshold is measured (d'). The Lu/Dosher Perceptual Template Model (PTM) and the Barlow/Pelli Equivalent Noise Model (ENM) claim that the TvN (threshold vs. noise) curve is well fit by a separable function of the form: Th(Next,d')= CRF(d') (1+(Next /Neq)^p)^(1/p) where the contrast response function behaves as CRF(d')∼d'^(1/t) for d'Neq we found t∼1.5±0.3. This finding that the CRF shape depends on Next means that all separable models are inadequate. We also found that Neq was very close to the noise detection threshold.

Klein, S. Levi, D. (2007). Problems with modeling detection and identification of signals in noise [Abstract]. Journal of Vision, 7(15):73, 73a, http://journalofvision.org/7/15/73/, doi:10.1167/7.15.73. [CrossRef]
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×