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Volume 11, Issue 2
An Inverse Problem for the Burgers Equation

Guo-Qiang He & Y. M. Chen

J. Comp. Math., 11 (1993), pp. 103-112.

Published online: 1993-11

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  • Abstract

In this paper the Generalized Pulse-Spectrum Technique (GPST) is extended to solve an inverse problem for the Burgers equation. We prove that the GPST is equivalent in some sense to the Newton-Kantorovich iteration method. A feasible numerical implementation is presented in the paper and some examples are executed. The numerical results show that this procedure works quite well.

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@Article{JCM-11-103, author = {He , Guo-Qiang and Chen , Y. M.}, title = {An Inverse Problem for the Burgers Equation}, journal = {Journal of Computational Mathematics}, year = {1993}, volume = {11}, number = {2}, pages = {103--112}, abstract = {

In this paper the Generalized Pulse-Spectrum Technique (GPST) is extended to solve an inverse problem for the Burgers equation. We prove that the GPST is equivalent in some sense to the Newton-Kantorovich iteration method. A feasible numerical implementation is presented in the paper and some examples are executed. The numerical results show that this procedure works quite well.

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/9309.html} }
TY - JOUR T1 - An Inverse Problem for the Burgers Equation AU - He , Guo-Qiang AU - Chen , Y. M. JO - Journal of Computational Mathematics VL - 2 SP - 103 EP - 112 PY - 1993 DA - 1993/11 SN - 11 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/9309.html KW - AB -

In this paper the Generalized Pulse-Spectrum Technique (GPST) is extended to solve an inverse problem for the Burgers equation. We prove that the GPST is equivalent in some sense to the Newton-Kantorovich iteration method. A feasible numerical implementation is presented in the paper and some examples are executed. The numerical results show that this procedure works quite well.

Guo-Qiang He & Y. M.Chen. (1970). An Inverse Problem for the Burgers Equation. Journal of Computational Mathematics. 11 (2). 103-112. doi:
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