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Maximum likelihood identification of a heat diffusion process : a pole clustering effect

Leden, Bo (1976) In International Journal of Control 24(2). p.217-227
Abstract
Parametric models of a one-dimensional heat diffusion process are determined using the maximum likelihood method. The process is a linear, infinite dimensional system. Statistical teats indicate that the appropriate orders of the models obtained are relatively low. It is found empirically that successive terms in the modal expansion of the transfer function of the process, having gain factors of the same sign, are identified as a single term.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
International Journal of Control
volume
24
issue
2
pages
217 - 227
publisher
Taylor & Francis
external identifiers
  • scopus:0016986778
ISSN
0020-7179
DOI
10.1080/00207177608932817
language
English
LU publication?
no
id
e074838f-cc12-44a1-b79b-d5e98513df59
date added to LUP
2018-12-27 06:14:37
date last changed
2019-01-06 14:21:17
@article{e074838f-cc12-44a1-b79b-d5e98513df59,
  abstract     = {Parametric models of a one-dimensional heat diffusion process are determined using the maximum likelihood method. The process is a linear, infinite dimensional system. Statistical teats indicate that the appropriate orders of the models obtained are relatively low. It is found empirically that successive terms in the modal expansion of the transfer function of the process, having gain factors of the same sign, are identified as a single term.},
  author       = {Leden, Bo},
  issn         = {0020-7179},
  language     = {eng},
  number       = {2},
  pages        = {217--227},
  publisher    = {Taylor & Francis},
  series       = {International Journal of Control},
  title        = {Maximum likelihood identification of a heat diffusion process : a pole clustering effect},
  url          = {http://dx.doi.org/10.1080/00207177608932817},
  volume       = {24},
  year         = {1976},
}