Publication detail

Compression of Vehicle-Driving Data by Means of Orthogonal Bases

ŠIMEČEK, V. MIHÁLIK, O.

Original Title

Compression of Vehicle-Driving Data by Means of Orthogonal Bases

Type

conference paper

Language

English

Original Abstract

The paper deals with application of orthogonal bases in signal approximation with the aim of data compression in a vehicle driving simulator. Three different bases are tested: Discrete Fourier Basis, Discrete Cosine Basis, and Slepian Basis. Quality of signal approximation error is assessed in terms of global squared errors. Thus obtained numerical results suggest that Slepian Basis affords the sparsest representation of signals tested in this study. Therefore, a considerable reduction of required memory can be accomplished.

Keywords

signal, approximation, compression, Slepian sequences, DPSS

Authors

ŠIMEČEK, V.; MIHÁLIK, O.

Released

25. 4. 2023

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-6154-3

Book

Proceedings II of the 29 th Conference STUDENT EEICT 2023 Selected papers

Edition

1

ISBN

2788-1334

Periodical

Proceedings II of the Conference STUDENT EEICT

State

Czech Republic

Pages from

13

Pages to

16

Pages count

4

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf

BibTex

@inproceedings{BUT184283,
  author="Vít {Šimeček} and Ondrej {Mihálik}",
  title="Compression of Vehicle-Driving Data by Means of Orthogonal Bases",
  booktitle="Proceedings II of the 29 th Conference STUDENT EEICT 2023 Selected papers",
  year="2023",
  series="1",
  journal="Proceedings II of the Conference STUDENT EEICT",
  pages="13--16",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6154-3",
  issn="2788-1334",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf"
}