An iterative reweighted least-squares algorithm for the design of 2D IIR filters

We present a new method for optimizing two-dimensional IIR filters with respect to a p-norm error criterion, especially for large p, when quasi-equiripple filters are obtained. We combine a Gauss-Newton convexification of the criterion with the iterative reweighted least-squares (IRLS) algorithm. Stability is obtained by using 1-D or 2-D convex stability domains based on a positive realness description. A final optimization of the numerator, keeping the denominator fixed, allows more freedom in choosing the value of a key parameter.