Implementation of the transposed Farrow structure

The Farrow structure provides an efficient way to implement sampling rate increase between arbitrary sampling rates. However, in the case of sampling rate decrease the Farrow structure can only implement filters with poor anti-aliasing properties because the transfer zeros are clustered around the integer multiples of the input sampling rate and not around the multiples of the output sampling rate where aliasing components appear. This problem can be overcome by using the transposed Farrow structure with the transfer zeros clustered around the integer multiples of the output sampling rate. The aliasing components are attenuated using the same polynomial function as for the Farrow structure. The main difference is that this polynomial is determined using the output sampling period as the basic interval, instead of the input sampling period. This paper gives overview and compares two alternative implementation forms for the transposed Farrow structure.