eldo_user

Monte Carlo Analysis
MCCONV Extract Function
Examples
• In this example, the second extract returns a boolean value (1 or 0). It returns 1 when the
standard deviation of quantity GAIN_DB has converged to within ± (0.01 + 0.05 ),
where
is the average value of the STD taken from the last w=20 Monte Carlo runs.
.EXTRACT AC LABEL=GAIN_DB YVAL(VDB(OUT), 1MEG)
.EXTRACT MC LABEL=STDDEV_GAIN_DB_CONV
+ MCCONV(GAIN_DB, STD,SETTLING, 20, 0.01, 0.05)
• Similarly, a test on the standard deviation can be specified with the confidence
techniques:
.EXTRACT MC LABEL=STDDEV_GAIN_DB_CONV
+ MCCONV(GAIN_DB, STD, CONFIDENCE, 40, 0.95, 0.00, 0.01)
• In the next example, the first three .EXTRACT statements are taken into account, and all
three of them must have converged before the MCCONV() function returns 1.
.EXTRACT AC LABEL=GAIN_DB YVAL(VDB(OUT), 1MEG)
.EXTRACT AC LABEL=PHASE_DB YVAL(VP(OUT), 1MEG)
.EXTRACT DC LABEL=CC I(VDD)
.EXTRACT MC LABEL=STD_CONV MCCONV(ALL, STD, SETTLING, 20, 0.01,0.05)
Tolerance tuning is inefficient in this situation; instead, use the default values as much
as possible, for instance, the following syntax should give a first estimate of the
uncertainty:
.EXTRACT MC LABEL=MC_AVG_CONV MCCONV(ALL, AVG, CONFIDENCE)
Then, use the SAVE/RESTART feature to obtain more accurate estimates.
Related Topics
CONFIDENCE Technique
SETTLING Technique
Post-Analysis of Monte Carlo Simulations
Monte Carlo Analysis Examples
Eldo® User's Manual, 15.3 519