A NONITERATIVE ALGORITHM FOR DECONVOLUTION‐INVERSE FILTERING USING THE CHEBYSHEV MINIMAX NORM FOR THE APPROXIMATION ERROR: Part I: Theory

A new computational noniterative algorithm which gives the solution to a linear deconvolution‐inverse filtering problem is proposed and its properties are studied. It is proved, in some specific cases of input signal, that the algorithm discussed gives the solution, which is equal to that with the Chebyshev minimax norm for the approximation error. In a general case of input signal the solution obtained provides a good prompt for determining an “appropriate subsystem” of n + 1 linear equations of n unknowns, which directly gives the Chebyshev minimax norm based solution.