1988
DOI: 10.1088/0031-9155/33/11/005
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On the possibility of obtaining non-diffused proximity functions from cloud-chamber data: II. Maximum entropy and Bayesian methods

Abstract: Maximum entropy and Bayesian methods are applied to an inversion problem which consists of unfolding diffusion from proximity functions calculated from cloud-chamber data. The solution appears to be relatively insensitive to statistical errors in the data (an important feature) given the limited number of tracks normally available from cloud-chamber measurements. It is the first time, to our knowledge, that such methods are applied to microdosimetry.

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