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Discrete piecewise monotonic approximation by a strictly convex distance function

1995
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Mathematics of Computation
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Theory and algorithms are presented for the following smoothing problem. We are given n measurements of a real-valued function that have been altered by random errors caused by the deriving process. For a given integer k , some efficient algorithms are developed that approximate the data by minimizing the sum of strictly convex functions of the errors in such a way that the approximated values are made up of at most k monotonie sections. If k = 1, then the problem can be solved by a special

doi:10.1090/s0025-5718-1995-1270617-x
fatcat:lwo5mhuprvgwngwh5aq3f3avwe