In this paper we present a new kind of algorithm, for finding a
solution

of the
system:
where

and

are multivariate polynomials of a
certain degree, in the variables

. The
algorithm is based on a multivariate interpolation approach, which
is a straightforward extension of the univariate algorithm of Van
Barel and Bultheel [
15]. In their approach interpolation
points are added one after each other, taking into account the
degree structure of the solution. In this paper, exactly the same is
done, for solving multivariate interpolation problems. Every step a
new interpolation point is introduced, so that the intermediate
result satisfies all the previous interpolation conditions and also
the new added one. After having added enough interpolation points we
will have the solution. Another difference between the univariate
and the multivariate approach, is the number of variables and their
combinations. In the multivariate case we can have a lot of
monomials of the same global degree but having different degrees in
each variable, and these degrees play an important role in for
example algebraic geometry.
We mentioned that we search for a solution of the system (not a
unique solution), but in fact we get even more, we get a set of
polynomial vectors which generate the module of all the solutions.
An implementation of the algorithm is made in Maple and we tested it
for some different multivariate examples, varying the number of
unknowns and their degree structure.
Keywords: multivariate interpolation, multivariate polynomials,
updating algorithm, module of solution vectors, pivoting