An Allan Variance Computation From Very Large
Datasets

Kunz, Jan

An Allan Variance Computation From Very Large Datasets

but.event.date	26.04.2018	cs
but.event.title	Student EEICT 2018	cs
dc.contributor.author	Kunz, Jan
dc.date.accessioned	2019-03-04T10:05:53Z
dc.date.available	2019-03-04T10:05:53Z
dc.date.issued	2018	cs
dc.description.abstract	This paper deals with calculating an Allan variance from a large datasets, which does not fit into a RAM memory. For this reason a parallel method is implemented in LabVIEW 2015 and tested on four different configurations of personal computer. An execution time was measured for a dataset of 2 754 448 000 samples. The time varies in dependence on calculated samples and the configuration of the computer. For the faster computers execution takes several minutes, whereas on the slower one the longest tested calculation of 100 samples per decade takes about two hours, which is still practical.	en
dc.format	text	cs
dc.format.extent	363-367	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Proceedings of the 24th Conference STUDENT EEICT 2018. s. 363-367. ISBN 978-80-214-5614-3	cs
dc.identifier.isbn	978-80-214-5614-3
dc.identifier.uri	http://hdl.handle.net/11012/138257
dc.language.iso	en	cs
dc.publisher	Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.relation.ispartof	Proceedings of the 24th Conference STUDENT EEICT 2018	en
dc.relation.uri	http://www.feec.vutbr.cz/EEICT/	cs
dc.rights	© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.rights.access	openAccess	en
dc.subject	Allan variance	en
dc.subject	large file	en
dc.subject	MEMS	en
dc.subject	gyroscope	en
dc.title	An Allan Variance Computation From Very Large Datasets	en
dc.type.driver	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en
eprints.affiliatedInstitution.department	Fakulta elektrotechniky a komunikačních technologií	cs

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