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Identification of parameters in distributed parameter systems by regularization

Kravaris, Costas and Seinfeld, John H. (1983) Identification of parameters in distributed parameter systems by regularization. In: 22nd IEEE Conference on Decision and Control. IEEE , Piscataway, NJ, pp. 50-55. https://resolver.caltech.edu/CaltechAUTHORS:20170727-163809593

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Abstract

Identification of spatially varying parameters in distributed parameter systems from noisy data is an ill-posed problem. The concept of regularization, widely used in solving linear Fredholm integral equations, is developed for the identification of parameters in distributed parameter systems. A general regularization identification theory is first presented and then applied to a parabolic identification problem. Methods for the numerical implementation of the regularization identification approach are also presented.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CDC.1983.269793DOIArticle
http://ieeexplore.ieee.org/document/4047503/PublisherArticle
ORCID:
AuthorORCID
Seinfeld, John H.0000-0003-1344-4068
Additional Information:© 1983 IEEE.
Record Number:CaltechAUTHORS:20170727-163809593
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170727-163809593
Official Citation:C. Kravaris and J. H. Seinfeld, "Identification of parameters in distributed parameter systems by regularization," The 22nd IEEE Conference on Decision and Control, San Antonio, TX, USA, 1983, pp. 50-55. doi: 10.1109/CDC.1983.269793
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79515
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:28 Jul 2017 16:09
Last Modified:03 Oct 2019 18:20

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