DocumentCode :
813646
Title :
Estimation of parameters in a partially whitened representation of a stochastic process
Author :
Kashyap, R.L.
Author_Institution :
Purdue University, Lafayette, IN, USA
Volume :
19
Issue :
1
fYear :
1974
fDate :
2/1/1974 12:00:00 AM
Firstpage :
13
Lastpage :
21
Abstract :
For a process which may not obey a stochastic linear difference equation (SDE) excited by white noise (i.e., ARMA equation), we will develop an SDE of prespecified order ( n,m ), excited by an "approximate white" noise. (The sense of approximation will be made precise in the text.) The corresponding representation is called the partially whitened representation (PWR) of order ( n,m ) for the process. A recursive method of parameter estimation is presented, and the accuracy of the estimates will be determined by analytical and simulation methods. The algorithm will asymptotically converge to the vector of coefficients of the ARMA ( n,m ) equation for the process, provided the process obeys such an equation. Otherwise, the algorithm will converge to the vector of coefficients of the PWR of order ( n,m ) for the process.
Keywords :
Autoregressive processes; Moving-average processes; Parameter estimation; Recursive estimation; Stochastic processes; Analytical models; Convergence; Difference equations; Filters; Parameter estimation; Recursive estimation; Stochastic processes; Stochastic resonance; White noise;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1974.1100459
Filename :
1100459
Link To Document :
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