Abstract
In this paper we study several different methods, both deterministic and stochastic, to solve the nuclear magnetic resonance relaxometry problem. This problem is strongly related to finding a non-negative function given a finite number of values of its Laplace transform embedded in noise. Some of the methods considered here are new. We also propose a procedure which exploits and combines the main features of these methods. Finally, to show the performance of this procedure, some results of applying it to synthetic data are reported.
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