Journal of Automation and Information Sciences
Published 12 issues per year
ISSN Print: 1064-2315
ISSN Online: 2163-9337
SJR:
0.173
SNIP:
0.588
CiteScore™::
2
Indexed in
Problems of Interpretation and Experimental Data Assimilation
Volume 40,
Issue 7, 2008,
pp. 26-36
DOI: 10.1615/JAutomatInfScien.v40.i7.30
ABSTRACT
Most of inverse problems dealing with interpretation of data obtained in experiment are known as ill-posed ones. Using regularization approach consideration was given to the statements of these problems based on the variational principle. This allows one to obtain approximate solutions which are consistent with errors in initial data and moreover, to perform measurement data assimilation into a mathematical model of the object under investigation.
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