Title :
The reversibility condition for elementary bilinear time-series model based on output sequence alone
Author_Institution :
Inst. of Automatics, Silesian Univ. of Technol., Gliwice, Poland
Abstract :
Reversibility of elementary bilinear time-series model is very important issue in parametric model identification based on minimisation of mean square value of prediction error. The reason is that estimation of parameters of irreversible time-series model is irreversible it is difficult. There is already very well known mathematical reversibility condition expressed as a function of the model´s coefficient, which has to be identified. The paper contains a discussion of simple condition, which can provide information about model´s reversibility before its identification.
Keywords :
bilinear systems; identification; mean square error methods; time series; elementary bilinear time-series model; mathematical reversibility condition; mean square value; output sequence; parametric model identification; prediction error; Analytical models; Computational modeling; Indexes; Mathematical model; Predictive models; Stability analysis; Time series analysis;
Conference_Titel :
Methods and Models in Automation and Robotics (MMAR), 2011 16th International Conference on
Conference_Location :
Miedzyzdroje
Print_ISBN :
978-1-4577-0912-8
DOI :
10.1109/MMAR.2011.6031366