The solution of discrete convolutions with a bounded error constraint

A. Arcese · 2005

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.

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