The maximum entropy method on the mean: Applications to linear programming and superresolution
F Gamboa, E Gassiat - Mathematical programming, 1994 - Springer
F Gamboa, E Gassiat
Mathematical programming, 1994•SpringerIn this paper, we give two different results. We propose new methods to solve classical
optimization problems in linear programming. We also obtain precise quantitative results for
the superresolution phenomenon, as observed earlier by practical searchers on specific
algorithms. The common background of our work is the generalized moment problem, which
is known to be connected with linear programming and superresolution. We describe the
Maximum Entropy Method on the Mean that provides solution to the problem and leads to …
optimization problems in linear programming. We also obtain precise quantitative results for
the superresolution phenomenon, as observed earlier by practical searchers on specific
algorithms. The common background of our work is the generalized moment problem, which
is known to be connected with linear programming and superresolution. We describe the
Maximum Entropy Method on the Mean that provides solution to the problem and leads to …
Abstract
In this paper, we give two different results. We propose new methods to solve classical optimization problems in linear programming. We also obtain precise quantitative results for the superresolution phenomenon, as observed earlier by practical searchers on specific algorithms. The common background of our work is the generalized moment problem, which is known to be connected with linear programming and superresolution. We describe the Maximum Entropy Method on the Mean that provides solution to the problem and leads to computational criteria to decide the existence of solutions or not.
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