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Monte Carlo Analysis<br />

Parameter Naming Conventions<br />

* ICARLO example<br />

.MODEL C CAP DEV=20%<br />

.MODEL R RES LOT=20% DEV=5%<br />

.MC 5 ALL<br />

V1 VIN 0 AC=1 DC=1<br />

R1 VIN A R 1k<br />

C1 A 0 C 10P<br />

.TRAN 20ns 20ns<br />

.PROBE V<br />

.EXTRACT tran file=test_out label=maxA max(v(A))<br />

.EXTRACT tran file=icarlo_out {1+ICARLO}<br />

.end<br />

This will generate the following results in the icarlo_out file:<br />

TITLE * ICARLO example<br />

EXTRACT for TRANSIENT ANALYSIS<br />

TEMPERATURE = 2.7000E+01 Celsius<br />

ICARLO = 0<br />

*{1+ICARLO} = 1.0000E+00<br />

TITLE * ICARLO example<br />

EXTRACT for TRANSIENT ANALYSIS<br />

TEMPERATURE = 2.7000E+01 Celsius<br />

ICARLO = 1<br />

*{1+ICARLO} = 2.0000E+00<br />

...<br />

Related Topics<br />

Monte Carlo Analysis Examples<br />

Example 17—Monte Carlo Sensitivity of a Two-Stage Operational Amplifier<br />

Parameter Naming Conventions<br />

This topic describes the naming conventions for the identification of statistical parameters. It is<br />

necessary to use these conventions in a sensitivity analysis to identify the significant circuit<br />

parameters.<br />

As an example, if X is a uniform random variable defined on the interval [−1, 1] then the<br />

variable Y = function(X) is a dependent variable obtained by simulating the uniform variable<br />

and applying a given transformation. The following example models a voltage dependent<br />

resistor, with a linear dependence with respect to the uniform random variable RSH,<br />

.PARAM W=1U L=1U<br />

.PARAM RSH=AUNIF(1K,100,1)<br />

.PARAM B1=-0.4 B2=8U<br />

R1 A B ’RSH*L/W*(1+B1*(TANH(B2*ABS(V(A,B)/L))))’<br />

In this section, the RC Wire model is used to demonstrate the effect of various formulations that<br />

combine local and global variations. The LEVEL parameter is set to LEVEL=3 for the RC wire<br />

model. The expression of the wire resistance is given by:<br />

536<br />

Eldo® User's Manual, 15.3

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