The solution of discrete convolutions with a bounded error constraint

In this paper, we give an algorithm for solving discrete convolutions with a bounded error constraint. Unlike least squares, the algorithm does not require inverting or forming the elements of a matrix but, rather, operates directly on the data. The algorithm is demonstrated for the prediction equation. Numerical results are presented for a second-order Butterworth filter.