A Convex Approach to Frisch-Kalman Problem

Di Zhao, Anders Rantzer, Li Qiu

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Sammanfattning

This paper proposes a convex approach to the Frisch-Kalman problem that identifies the linear relations among variables from noisy observations. The problem was proposed by Ragnar Frisch in 1930s, and was promoted and further developed by Rudolf Kalman later in 1980s. It is essentially a rank minimization problem with convex constraints. Regarding this problem, analytical results and heuristic methods have been pursued over a half century. The proposed convex method in this paper is demonstrated to outperform several commonly adopted heuristics when the noise components are relatively small compared with the underlying data.

Originalspråkengelska
Titel på gästpublikation2019 IEEE 58th Conference on Decision and Control, CDC 2019
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor7154-7158
Antal sidor5
ISBN (elektroniskt)9781728113982
ISBN (tryckt)978-1-7281-1399-9
DOI
StatusPublished - 2020 mar 12
Evenemang58th IEEE Conference on Decision and Control, CDC 2019 - Nice, Frankrike
Varaktighet: 2019 dec 112019 dec 13

Publikationsserier

NamnProceedings of the IEEE Conference on Decision and Control
FörlagIEEE
Volym2019-December
ISSN (tryckt)0743-1546
ISSN (elektroniskt)2576-2370

Konferens

Konferens58th IEEE Conference on Decision and Control, CDC 2019
Land/TerritoriumFrankrike
OrtNice
Period2019/12/112019/12/13

Ämnesklassifikation (UKÄ)

  • Beräkningsmatematik
  • Signalbehandling

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