Conditional Stability and Numerical Reconstruction of Initial Temperature
Author(s) -
Jingzhi Li,
Masahiro Yamamoto,
Jun Zou
Publication year - 2008
Publication title -
communications on pure andamp applied analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.077
H-Index - 42
eISSN - 1553-5258
pISSN - 1534-0392
DOI - 10.3934/cpaa.2009.8.361
Subject(s) - tikhonov regularization , discretization , regularization (linguistics) , finite element method , inverse problem , stability (learning theory) , mathematics , convergence (economics) , domain (mathematical analysis) , mathematical optimization , computer science , mathematical analysis , physics , artificial intelligence , machine learning , economics , thermodynamics , economic growth
In this paper, we address an inverse problem of reconstruction of the initial temperature in a heat conductive system when some measurement data of temperature are available, which may be observed in a subregion inside or on the boundary of the physical domain, along a time period which may start at some point, possibly far away from the initial time. A conditional stability estimate is flrst achieved by the Carleman estimate for such recon- struction. Numerical reconstruction algorithm is proposed based on the out- put least-squares formulation with the Tikhonov regularization using the flnite element discretization, and the existence and convergence of the flnite element solution are presented. Numerical experiments are carried out to demonstrate the applicability and efiectiveness of the proposed method.
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