  This paper is concerned with the problem of designing computationally
efficient Generalized Comb Filters (GCF). Basically, GCF filters are
anti-aliasing filters that guarantee superior performance in terms of
selectivity and quantization noise rejection compared to classical comb
filters, when used as decimation filters in multistage architectures. Upon
employing a partial polyphase (PP) architecture proposed in a companion paper,
we develop a sensitivity analysis in order to investigate the effects of the
coefficients' quantization on the frequency response of the designed filters.
We show that the sensitivity of the filter response to errors in the
coefficients is dependent on the particular split of the decimation factor
between the two sub-filters constituting the PP architecture. The sensitivity
analysis is then used for developing a fixed-point implementation of a sample
filter from the class of GCF filters, used as reference filter throughout the
paper. Finally, we present computer simulations in order to evaluate the
performance of the designed fixed-point filters.
