Modeling and Simulation: Proceedings of the ... Annual Pittsburgh Conference, Volume 10Instrument Society of America, 1979 - Computer simulation |
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Page 202
... discrimination of its components . In collaboration with Lynn Olzak , we have gathered data on these four detection and discrimination tasks . X and Y were sine wave gratings of 3 and 12 cycles per degree , respectively . The gratings ...
... discrimination of its components . In collaboration with Lynn Olzak , we have gathered data on these four detection and discrimination tasks . X and Y were sine wave gratings of 3 and 12 cycles per degree , respectively . The gratings ...
Page 203
... discrimination of the components were always measured on the same day . There were two observers ( J. Thomas and L. Olzak ) . We have 17 sets of such data . Performance , as measured by area under the ROC , is better for discrimination ...
... discrimination of the components were always measured on the same day . There were two observers ( J. Thomas and L. Olzak ) . We have 17 sets of such data . Performance , as measured by area under the ROC , is better for discrimination ...
Page 272
... discrimination . That is , in this case the parameters in the model are fixed by basic psychophysical experi- ments and the equivalent sine - wave contrast for the edge can be computed exactly . For a one - dimensional edge transition ...
... discrimination . That is , in this case the parameters in the model are fixed by basic psychophysical experi- ments and the equivalent sine - wave contrast for the edge can be computed exactly . For a one - dimensional edge transition ...
Contents
BIOMEDICAL | 4 |
MATHEMATICAL MODELING OF INTRACRANIAL PRESSURE DYNAMICS I | 11 |
QUANTITATIVE ASSESSMENT | 11 |
Copyright | |
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algorithm amino acid amino acid sequences amplitude analysis ARA-C ARMA model AVOD bandwidth biological cell cycle cerebrospinal fluid CFU-C classification cluster codon compartment components constant contrast CSF pressure detection developed DIFFUSION CHAMBER discrimination distribution DNA base DNA sequences dose drug dynamics effect equations estimated experimental factor Figure filter flow formation Fourier hepatic encephalopathy increases informational structure inhibition input intracranial pressure kinetic lateral inhibition line spread function linear luminance Mach band mathematical mechanisms method MODELING AND SIMULATION mRNA msec muscle neurons Nicolini noise nonlinear normal observed obtained optimal order kernel outflow resistance output parameters patients pattern percent phase Pittsburgh predicted protein protoplasts ramp slope receptive fields response saccade sample shown signal spatial frequency specimens stimulus technique theory threshold tion tissue treatment tRNA University values variables volume width