A new eigenfilter based on total least squares error criterion

In this paper, a new eigenfilter based on total least squares error criteri on is investigated. The filter coefficients are obtained from the elements of the eigenvector corresponding to minimum eigenvalue of a real, symmetric and positive definite matrix. Four features of new method are given below. First, the computation of filter coefficients of new eigenfilter is more n umerically stable than that of the least-squares method whose solution is o btained by solving matrix inverse, Second, new eigenfilter does not need a reference frequency point for normalization as done in traditional eigenfil ter, Third, the solution of the new eigenfilter is closer to the solution o f the least-squares method than one of the conventional eigenfilter, Fourth , the proposed method is easy to incorporate with linear constraints and ca n be extended to design equiripple and two dimensional linear phase filters . Several design examples are used to illustrate the effectiveness of this new design approach.