In many practical problems, we need to use interpolation: we know that the value of a quantity is uniquely determined by some other quantity x (i.e., y = f(x)), we have measured several pairs of values (xi, yi), and we want to predict y for a given x. We can only guarantee estimates for y if we have some a priori information about the function f(x). In particular, in some problems, we know that f(x) is a polynomial of known degree d (e.g., that it is linear, or that it is quadratic). For this polynomial interpolation, with interval uncertainty of the input data (xi, yi), we present several reasonable algorithms that compute, for a given x0, guaranteed bounds for f(x0).
Reliable Computing – Springer Journals
Published: Oct 6, 2004
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