title: 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.
authors.affiliation: Radiological Research Laboratories, College of Physicians & Surgeons of Columbia University, New York, NY 10032.
authors.forename: M
authors.initials: M
authors.lastname: Zaider
authors.forename: G N
authors.initials: GN
authors.lastname: Minerbo
mesh_terms: D001499:Bayes Theorem; D011874:Radiometry / Q000295:instrumentation / Q000379:methods