Least-Squares and Minimax Design of Polynomial Impulse Response FIR Filters for Reconstruction of Two-Periodic Nonuniformly Sampled Signals

This paper proposes polynomial impulse response finite-impulse response filters for reconstruction of two-periodic nonuniformly sampled signals. The foremost advantages of using these reconstruction filters are that on-line filter design thereby is avoided and subfilters with fixed dedicated multipliers can be employed in an implementation. The overall implementation cost can in this way be reduced substantially in applications where the sampling pattern changes from time to time. The paper presents two different design techniques that yield optimum filters in the least-squares and minimax senses, respectively. Design examples are included that illustrate the benefits of the proposed filters