A typical process has a large number of control parameters that can
have a significant impact on the performance of the circuit as well
as on the yield of the product.
To establish a basic knowledge of the behavior of a design under variation of
input parameter values and to estimate the relative importance of the
input parameters, sensitivity analysis applies small changes
to the nominal values of input parameters according to an axial design
scheme.
For measurements and numerical simulation, variations of the input
parameter values cannot be made infinitely small.
The sensitivity of an output variable 
with respect to an input
parameter 
is therefore defined as
,
with 
sufficiently small.
In order to compensate for highly nonlinear system responses,
it is useful to transform the input parameters appropriately before
computing sensitivity numbers.
For example, the dose parameter of most ion implantation steps
exhibit a logarithmic influence on the device behavior; to obtain
comparable sensitivity data, is computed from 
instead of x, x being the dose setting in 
.