Modeling and Simulation: Proceedings of the ... Annual Pittsburgh Conference, Volume 10Instrument Society of America, 1979 - Computer simulation |
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Page 114
... msec . spike epoch ends for the next threshold crossing . are marked by rectangular pulses and interpreted and stored by the program like a spike class , their features having been included along with the real spike shapes . Every 51 msec ...
... msec . spike epoch ends for the next threshold crossing . are marked by rectangular pulses and interpreted and stored by the program like a spike class , their features having been included along with the real spike shapes . Every 51 msec ...
Page 216
... msec , p = .1 and x2 ( t ) has △ = 15 msec , p = .3 . In both cases we take the stimulus to be a luminance pulse of 5 msec duration such that during the pulse the luminance goes to either twice the background level ( x = + L ) or to 0 ...
... msec , p = .1 and x2 ( t ) has △ = 15 msec , p = .3 . In both cases we take the stimulus to be a luminance pulse of 5 msec duration such that during the pulse the luminance goes to either twice the background level ( x = + L ) or to 0 ...
Page 218
... msec at scotopic levels to TM < 40 msec at photopic levels . With these definitions the first and second order kernels should be about the same size . Relationships such as and P n , T 2 2 ... y2 = 1 Σδη ( τ ) • Σôh ( t ) + p2 Σ sôh2 ...
... msec at scotopic levels to TM < 40 msec at photopic levels . With these definitions the first and second order kernels should be about the same size . Relationships such as and P n , T 2 2 ... y2 = 1 Σδη ( τ ) • Σôh ( t ) + p2 Σ sôh2 ...
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