Title
Discrete Lanczos derivatives of noisy data
Document Type
Article
Publication Title
International Journal of Computer Mathematics
Publication Date
5-1-2012
Abstract
Finite differences are frequently used to differentiate empirical functions, but standard differences tend to amplify the random error that is present in almost all empirical data. This paper uses higher-order Lanczos derivatives and discretized Legendre polynomials to generate minimum variance finite differences to approximate ordinary derivatives of all orders for a fixed discretization error magnitude. The resulting differences can be implemented as finite impulse response filters and are therefore very fast on a computer. © 2012 Taylor & Francis Group, LLC.
Volume
89
Issue
7
First Page
916
Last Page
931
DOI
10.1080/00207160.2012.666348
ISSN
00207160
E-ISSN
10290265
Recommended Citation
McDevitt, Timothy J., "Discrete Lanczos derivatives of noisy data" (2012). Faculty Publications. 1235.
https://jayscholar.etown.edu/facpubharvest/1235
