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A self-tuning predictor

Wittenmark, Björn LU (1974) In IEEE Transactions on Automatic Control 19(6). p.848-851
Abstract
An adaptive predictor for discrete time stochastic processes with constant but unknown parameters is described. The predictor which in real time tunes its parameters using the method of least squares is called a self-tuning predictor. The predictor has attractive asymptotic properties. If the parameter estimation converges and if the predictor contains parameters enough, then it will converge to the minimum square error predictor that could be obtained if the parameters of the process were known. The computations to be carried out at each sampling interval are very moderate and the algorithm is well suited for real-time applications. The self-tuning predictor can be used to predict processes which contain trends or periodic disturbances.... (More)
An adaptive predictor for discrete time stochastic processes with constant but unknown parameters is described. The predictor which in real time tunes its parameters using the method of least squares is called a self-tuning predictor. The predictor has attractive asymptotic properties. If the parameter estimation converges and if the predictor contains parameters enough, then it will converge to the minimum square error predictor that could be obtained if the parameters of the process were known. The computations to be carried out at each sampling interval are very moderate and the algorithm is well suited for real-time applications. The self-tuning predictor can be used to predict processes which contain trends or periodic disturbances. Further, the algorithm can easily be modified in order to make it possible to predict processes with slowly time-varying parameters. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Automatic Control
volume
19
issue
6
pages
848 - 851
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • Scopus:0016355559
ISSN
0018-9286
DOI
10.1109/TAC.1974.1100734
language
English
LU publication?
yes
id
4feab4bf-4e2f-4468-bb4d-120aad9de09f (old id 4857032)
date added to LUP
2014-12-04 11:59:09
date last changed
2016-04-16 11:43:28
@misc{4feab4bf-4e2f-4468-bb4d-120aad9de09f,
  abstract     = {An adaptive predictor for discrete time stochastic processes with constant but unknown parameters is described. The predictor which in real time tunes its parameters using the method of least squares is called a self-tuning predictor. The predictor has attractive asymptotic properties. If the parameter estimation converges and if the predictor contains parameters enough, then it will converge to the minimum square error predictor that could be obtained if the parameters of the process were known. The computations to be carried out at each sampling interval are very moderate and the algorithm is well suited for real-time applications. The self-tuning predictor can be used to predict processes which contain trends or periodic disturbances. Further, the algorithm can easily be modified in order to make it possible to predict processes with slowly time-varying parameters.},
  author       = {Wittenmark, Björn},
  issn         = {0018-9286},
  language     = {eng},
  number       = {6},
  pages        = {848--851},
  publisher    = {ARRAY(0x9636108)},
  series       = {IEEE Transactions on Automatic Control},
  title        = {A self-tuning predictor},
  url          = {http://dx.doi.org/10.1109/TAC.1974.1100734},
  volume       = {19},
  year         = {1974},
}