Decomposition and Regularization of the Solution of Ill-Posed Inverse Problems of Processing Measurement Information. Part 3. Experimental Confirmation of Theory


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

Experimental confirmation of the adaptive theory of recognition and stable determination of information components as part of a given vector of estimated parameters of an ill-posed inverse problem that arises in the processing of measurement information is presented. The experiment is based on numerical simulation of the problem of determining the parameters of a transformation of the coordinates of the points of a satellite geodetic network into the state coordinate basis by means of a decomposition model. The advantages of the Helmert decomposition model and an adaptive regularization algorithm for stable estimation of the information regularization parameters for stable estimation of the information parameters of a transformation by comparison with the initial Helmert model are confirmed.

作者简介

Yu. Surnin

Siberian State University of Geosystems and Technologies

编辑信件的主要联系方式.
Email: surnin@ssga.ru
俄罗斯联邦, Novosibirsk

补充文件

附件文件
动作
1. JATS XML

版权所有 © Springer Science+Business Media, LLC, part of Springer Nature, 2019