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Programs for signal recovery from noisy data using the maximum likelihood principle II. Program implementation
datasetposted on 06.12.2019 by V.I. Gelfgat, E.L. Kosarev, E.R. Podolyak
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Abstract Three subroutines intended for nonnegative signal recovery from noisy experimental data distorted by the measuring device are presented. The use of these subroutines is illustrated by a test program. Title of program: MLG8, MLU8, MLP8 Catalogue Id: ACLJ_v1_0 Nature of problem A program package for non-negative signal recovery from noisy experimental data distorted by the measuring device is presented. Noise may have a Gaussian, binomial or Poissonian distribution at each experimental point. Three examples are given which demonstrate the usage of the package: a) reduction to an arbitrary instrumental function, which depends only on the difference of its arguments (this is the typical spectroscopic problem); b) the expansion of an exponentially decaying curve which has ... Versions of this program held in the CPC repository in Mendeley Data ACLJ_v1_0; MLG8, MLU8, MLP8; 10.1016/0010-4655(93)90018-8 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)