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Generalization of the Total Variance Approach to the Different Classes of Structure Functions

Published

Author(s)

Francois Vernotte, David A. Howe

Abstract

The Total variance approach has been developed for in-creasing the confidence of the estimation of the classical Allan variance (AVAR), particularly for large integration time values. This method is based on a procedure of extension of the original data sequence called the mirror- reflection which increases the equivalent degrees of freedom of each Allan variance estimate. Recently, we applied this approach to the Modified Allan variance (MVAR) and proved that, in this case, an-other procedure of extension of the data sequence should be used: the reflection- only extension.
Proceedings Title
Proceedings of 2000 EFTF Conference
Conference Location
, US

Citation

Vernotte, F. and Howe, D. (2000), Generalization of the Total Variance Approach to the Different Classes of Structure Functions, Proceedings of 2000 EFTF Conference, , US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=920082 (Accessed April 16, 2024)
Created February 29, 2000, Updated October 12, 2021