L/sub 2/-sensitivity minimization of one- and two-dimensional state-space digital filters subject to L/sub 2/-scaling constraints

Abstract

This paper investigates the problem of minimizing an L/sub 2/-sensitivity measure subject to L/sub 2/-norm dynamic-range scaling constraints for one-dimensional (1-D) as well as a class of two-dimensional (2-D) state-space digital filters, where the 2-D digital filters are described by a transposed structure of the Fornasini-Marchesini second local state-space model. In each case, a novel iterative technique is developed to solve the constraint optimization problem directly. The proposed solution methods are largely based on the use of a Lagrange function and some matrix-theoretic techniques. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.