eldo_user

Five independent random variables will be created in the sampling:
• The variable PP(VAR,GLOBVAR) with global variations.
Monte Carlo Analysis
Parameter Naming Conventions
• The two variables PE(LOCVAR,R1,W) and PE(LOCVAR,R2,W) which come from the
statement LOCVAR=AUNIF(0U,0.02U).
• The two variables PE(VAR,R1,L) and PE(VAR,R2,L).
Macro PM(.)
Consider the following statements:
.PARAM VAR=AUNIF(0U,0.05U)
.PARAM BIAS=1M
I1 0 1 BIAS
I2 0 2 BIAS
R1 1 0 RESISTOR
R2 2 0 RESISTOR
.MODEL RESISTOR R LEVEL=3 W=3U L=3U RSH=100 DW=VAR DLR=VAR
This example is another application of the previous implicit rule on variations. The parameter
VAR has DEV variations, and it is used two times in the .MODEL definition. Two random
variables are associated to this model, but these variables are global for the circuit, because the
model has a global scope. The resistors R1 and R2 will share the same random variables.
The macro PM(.) was introduced for referencing these random variables. In this example, we
have two independent variables: PM(VAR,RESISTOR,DW) and PM(VAR,RESISTOR,DL).
The syntax is defined as follows:
PM(parameter_name, model_name, model_parameter)
The random variable that affects the model parameter model_parameter associated to the model
model_name is such that its distribution is specified in the definition of the parameter
parameter_name.
It is important to note that the variables PM(VAR,RESISTOR,DW) and
PM(VAR,RESISTOR,DL) have the same distribution. The previous lines are strictly equivalent
to the following (from the mathematical view):
Eldo® User's Manual, 15.3 539