Detail publikačního výsledku

An Allana Variance Computation from Very Large Datasets

KUNZ, J.

Originální název

An Allana Variance Computation from Very Large Datasets

Anglický název

An Allana Variance Computation from Very Large Datasets

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

Allan variance, large file, MEMS, gyroscope

Klíčová slova v angličtině

Allan variance, large file, MEMS, gyroscope

Autoři

KUNZ, J.

Rok RIV

2019

Vydáno

26.04.2018

Místo

Brno

ISBN

978-80-214-5614-3

Kniha

Proceedings of the 24 th Conference STUDENT EEICT 2018

Strany od

363

Strany do

367

Strany počet

5

BibTex

@inproceedings{BUT147184,
  author="Jan {Kunz}",
  title="An Allana Variance Computation from Very Large Datasets",
  booktitle="Proceedings of the 24 th  Conference STUDENT EEICT 2018",
  year="2018",
  pages="363--367",
  address="Brno",
  isbn="978-80-214-5614-3"
}

Dokumenty

EEICT_Kunz