Proceedings of the 1975 Winter Simulation Conference: December 18-19, 1975, Sacramento, California |
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Page 242
... function must be transformed into a cumulative distribution function . Given a random value ( RN ) from a 01 uniformly distributed population , the inverse of the cumulative distribution function is then used to compute a corresponding ...
... function must be transformed into a cumulative distribution function . Given a random value ( RN ) from a 01 uniformly distributed population , the inverse of the cumulative distribution function is then used to compute a corresponding ...
Page 457
... functions of three or more variables . Typically the required function generation will be done on the digital computer using table lookup and linear interpolation , and the rest of the compu- tation , including integration , will be ...
... functions of three or more variables . Typically the required function generation will be done on the digital computer using table lookup and linear interpolation , and the rest of the compu- tation , including integration , will be ...
Page 725
... function is approximated in the one dimensional Schrödinger equation by a step function with an arbitrary , finite number of steps . In each step the resulting differential equation has constant coefficients and is integrated exactly in ...
... function is approximated in the one dimensional Schrödinger equation by a step function with an arbitrary , finite number of steps . In each step the resulting differential equation has constant coefficients and is integrated exactly in ...
Contents
Business Oriented Simulation System BOSS | 11 |
G K Hutchinson | 25 |
BIOMEDICAL SIMULATION I | 59 |
Copyright | |
37 other sections not shown
Common terms and phrases
activity aircraft allocated analog analog computer analysis block California State University cell age distribution cell DNA COBOL computer simulation cost cycle decision defined demand determined developed DNA distribution dynamic effect elements energy entity equations estimates evaluation event example execution experimental eye movement facilities factors flow FORTRAN frequency function GPSS hardware hippocampus hybrid computer initial input instructions interaction JOGGING/RUNNING load loop macro matrix maximum memory missile modules node normal operation output parameters performance plot point spread function problem pyramidal cells queue random random variable represent resource saccadic sampling scheduled sequence shown in Figure signal SIMSCRIPT SIMTRAN simulation language simulation model specified star statistics storage structure subroutine System/3 Table techniques terminal tion triangular distribution utility variables WATS wave