DocumentCode :
486841
Title :
Identification of Linear Stochastic Systems via Cumulant Matching
Author :
Tugnait, Jitendra K.
Author_Institution :
Long Range Research Division, Exxon Production Research Company, P. O. Box 2189, Houston, Texas 77001
fYear :
1986
fDate :
18-20 June 1986
Firstpage :
2087
Lastpage :
2092
Abstract :
The problem of identification of time-invariant, single-input single-output, linear stochastic systems driven by non-Gaussian white noise is considered. The system is not restricted to be minimum phase and moreover, it is allowed to contain all-pass components. A least squares criterion that involves matching the second and the fourth order cumulant functions of the noisy observations is proposed. Knowledge of the probability distribution of the driving noise is not required. An order determination criterion that is a modification of the well known Akaike information criterion is also proposed. Strong consistency of the proposed estimator is proved under certain sufficient conditions. Simulation results are also presented to illustrate the method.
Keywords :
Least squares methods; Parameter estimation; Probability distribution; Production systems; Statistics; Stochastic systems; Sufficient conditions; System identification; Transfer functions; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 1986
Conference_Location :
Seattle, WA, USA
Type :
conf
Filename :
4789275
Link To Document :
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