Why Modified exponential covariance kernel is empirically successful
A theoretical explanation
Abstract
It is known that in the first approximation, many real-life stationary stochastic processes are well- described by an exponential covariance kernel C(u) = exp(-a|u|). Empirical evidence shows that in many practical situations, a good second approximation is provided by the modified exponential covari- ance kernel C(u) = exp(-a |u|) (1-r|u|). In this paper, we provide a theoretical explanation for this empirical phenomenon.
Details
- Externe Organisation(en)
-
University of Texas at El Paso
The University of Liverpool
- Typ
- Artikel
- Journal
- Journal of Uncertain Systems
- Band
- 10
- Seiten
- 10-14
- Anzahl der Seiten
- 5
- ISSN
- 1752-8909
- Publikationsdatum
- 02.2016
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Maschinelles Sehen und Mustererkennung, Steuerung und Optimierung, Artificial intelligence
- Elektronische Version(en)
-
http://www.worldacademicunion.com/journal/jus/jusVol10No1paper02.pdf (Zugang:
Offen
)
