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Regularized Solutions to the Aerosol Data Inversion Problem

Wolfenbarger, J. Kenneth and Seinfeld, John H. (1991) Regularized Solutions to the Aerosol Data Inversion Problem. SIAM Journal on Scientific and Statistical Computing, 12 (2). pp. 342-361. ISSN 0196-5204. doi:10.1137/0912019.

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Regularized solutions to the aerosol data inversion problem are presented. An approximate form of generalized cross validation is developed that is applicable to this linearly constrained inverse problem. The results obtained with this algorithm for choosing the smoothing parameter are compared with those obtained by the method of discrepancy and by minimizing an unbiased estimate of the inverted errors. Examples are presented that demonstrate the importance of using generalized cross validation to choose the smoothing parameter when the magnitude of the errors in the data is difficult to estimate.

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Seinfeld, John H.0000-0003-1344-4068
Additional Information:This research was supported by National Science Foundation grant ATM-8503103.
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Issue or Number:2
Record Number:CaltechAUTHORS:20230302-260631600.1
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:119625
Deposited By: Tony Diaz
Deposited On:03 Mar 2023 16:05
Last Modified:03 Mar 2023 16:05

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