SVD-based design and new structures for variable fractional-delay digital filters

This paper shows that the problem of designing one-dimensional (1-D) variable fractional-delay (VFD) digital filter can be elegantly reduced to the easier subproblems that involve one-dimensional (1-D) constant filter (subfilter) designs and I-D polynomial approximations. By utilizing the singular value decomposition (SVD) of the variable design specification, we prove that both I-D constant filters and 1-D polynomials possess either symmetry or anti-symmetry simultaneously. Therefore, a VFD filter can be efficiently obtained by designing I-D constant filters with symmetrical or antisymmetrical coefficients and performing 1-D symmetrical or antisymmetrical approximations. To perform the weighted-least-squares (WLS) VFD filter design, a new WLS-SVD method is also developed. Moreover, an objective criterion is proposed for selecting appropriate subfilter orders and polynomial degrees. Our computer simulations have shown that the SVD-based design and WLS-SVD design can achieve much higher design accuracy with significantly reduced filter complexity than the existing WLS design method. Another important part of the paper proposes two new structures for efficiently implementing the resulting VFD filter, which require less computational complexity than the so-called Farrow structure.