An efficient least-squares approach for the design of 1-D and 2-D FIR digital filters with complex coefficients

Abstract

An approach for the design of 1-D and 2-D FIR digital filters with complex coefficients is presented. In this approach, the error measure is formulated as a quadratic function and the filter coefficients are obtained by solving a set of linear equations. The proposed approach is more efficient than the eigenfilter approach regarding the amount of computation and design time. Moreover, the proposed approach leads to smaller least-squares errors. Design examples are included to illustrate the advantages of the approach.