Designing optimal sampling schemes for multi-dimensional data

Johan Swärd; Filip Elvander; Andreas Jakobsson

doi:10.1109/ACSSC.2017.8335468

Designing optimal sampling schemes for multi-dimensional data

Johan Swärd, Filip Elvander, Andreas Jakobsson

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.

Originalspråk	engelska
Titel på värdpublikation	2017 51st Asilomar Conference on Signals, Systems, and Computers
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	850-852
Antal sidor	3
ISBN (elektroniskt)	978-1-5386-1823-3
DOI	https://doi.org/10.1109/ACSSC.2017.8335468
Status	Published - 2017
Evenemang	51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017) - Asilomar, Pacific Grove, USA Varaktighet: 2017 okt. 29 → 2017 nov. 1

Konferens

Konferens	51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017)
Land/Territorium	USA
Ort	Pacific Grove
Period	2017/10/29 → 2017/11/01

Ämnesklassifikation (UKÄ)

Signalbehandling

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10.1109/ACSSC.2017.8335468

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title = "Designing optimal sampling schemes for multi-dimensional data",

abstract = "In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.",

author = "Johan Sw{\"a}rd and Filip Elvander and Andreas Jakobsson",

year = "2017",

doi = "10.1109/ACSSC.2017.8335468",

language = "English",

pages = "850--852",

booktitle = "2017 51st Asilomar Conference on Signals, Systems, and Computers",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017) ; Conference date: 29-10-2017 Through 01-11-2017",

}

Swärd, J , Elvander, F & Jakobsson, A 2017, Designing optimal sampling schemes for multi-dimensional data. i 2017 51st Asilomar Conference on Signals, Systems, and Computers . IEEE - Institute of Electrical and Electronics Engineers Inc., s. 850-852, 51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017), Pacific Grove, Kalifornien, USA, 2017/10/29. https://doi.org/10.1109/ACSSC.2017.8335468

Designing optimal sampling schemes for multi-dimensional data. / Swärd, Johan ; Elvander, Filip ; Jakobsson, Andreas.

2017 51st Asilomar Conference on Signals, Systems, and Computers . IEEE - Institute of Electrical and Electronics Engineers Inc., 2017. s. 850-852.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

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AU - Elvander, Filip

AU - Jakobsson, Andreas

PY - 2017

Y1 - 2017

N2 - In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.

AB - In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.

U2 - 10.1109/ACSSC.2017.8335468

DO - 10.1109/ACSSC.2017.8335468

M3 - Paper in conference proceeding

SP - 850

EP - 852

BT - 2017 51st Asilomar Conference on Signals, Systems, and Computers

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017)

Y2 - 29 October 2017 through 1 November 2017

ER -

Designing optimal sampling schemes for multi-dimensional data

Sammanfattning

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