Faculty Bibliography

This paper develops a new iterative reweighted least squares algorithm for the design of optimal L(p) approximation FIR filters. The algorithm combines a variable p technique with a Newton's method to give excellent robust initial convergence and quadratic final convergence. Details of the convergence properties when applied to the L(p) optimization problem are given. The primary purpose of L(p) approximation for filter design is to allow design with different error criteria in pass and stopband and to design constrained L(2) approximation filters. The new method can also be applied to the complex Chebyshev approximation problem and to the design of 2-D FIR filters.