  We present an extension of our GPGCD method, an iterative method for
calculating approximate greatest common divisor (GCD) of univariate
polynomials, to multiple polynomial inputs. For a given pair of polynomials and
a degree, our algorithm finds a pair of polynomials which has a GCD of the
given degree and whose coefficients are perturbed from those in the original
inputs, making the perturbations as small as possible, along with the GCD. In
our GPGCD method, the problem of approximate GCD is transferred to a
constrained minimization problem, then solved with the so-called modified
Newton method, which is a generalization of the gradient-projection method, by
searching the solution iteratively. In this paper, we extend our method to
accept more than two polynomials with the real coefficients as an input.
