A selftuning predictor
(1974) In IEEE Transactions on Automatic Control 19(6). p.848851 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 selftuning 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 realtime applications. The selftuning 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 selftuning 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 realtime applications. The selftuning 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 timevarying parameters. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/4857032
 author
 Wittenmark, Björn ^{LU}
 organization
 publishing date
 1974
 type
 Contribution to journal
 publication status
 published
 subject
 in
 IEEE Transactions on Automatic Control
 volume
 19
 issue
 6
 pages
 848  851
 publisher
 IEEEInstitute of Electrical and Electronics Engineers Inc.
 external identifiers

 Scopus:0016355559
 ISSN
 00189286
 DOI
 10.1109/TAC.1974.1100734
 language
 English
 LU publication?
 yes
 id
 4feab4bf4e2f4468bb4d120aad9de09f (old id 4857032)
 date added to LUP
 20141204 11:59:09
 date last changed
 20161013 04:57:51
@misc{4feab4bf4e2f4468bb4d120aad9de09f, 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 selftuning 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 realtime applications. The selftuning 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 timevarying parameters.}, author = {Wittenmark, Björn}, issn = {00189286}, language = {eng}, number = {6}, pages = {848851}, publisher = {ARRAY(0x96ad608)}, series = {IEEE Transactions on Automatic Control}, title = {A selftuning predictor}, url = {http://dx.doi.org/10.1109/TAC.1974.1100734}, volume = {19}, year = {1974}, }