ABSTRACT
Interpolation is the process of detennining the value of the dependent variable f corresponding to a particular value of the independent variable x when the functionf(x) is described by a set of tabular data. Inverse interpolation is the process of detennining the value of the independent variable x corresponding to a particular value of the dependent variable f In other words, inverse interpolation is evaluation of the inverse function x(f). Inverse interpolation can be accomplished by:
I. Fitting a polynomial to the inverse function xU) 2. Solving a direct polynomial f(x) iteratively for xU)
Fitting a polynomial to the inverse function x(f) appears to be the obvious approach. However, some problems may occur. The inverse function x(f) may not resemble a polynomial. The values offmost certainly are not equally spaced. In such cases, a direct fit polynomialf(x) may be preferred, even though it must be solved iteratively for x(f), for example, by Newton's method.
