Optimal finite impulse response approximate inverse of linear periodic filters

A method to construct an optimal finite impulse response (FIR) approximate inverse for discrete-time causal FIR periodic filters in the presence of measurement noise is proposed. The objective function to be minimised is the sum-of-mean-square errors over one period. On the basis of the matrix impulse response of the multi-input multi-output time-invariant representation of periodic filters, the optimisation problem is formulated as one that minimises the summed equation errors of a set of over-determined linear equations. It is shown that the problem is equivalent to a set of least-squares problems from which a simple, closed-form solution is obtained. Numerical examples are used to illustrate the performance of the proposed FIR approximate inverse.