IDENTIFICATION OF LINEAR STOCHASTIC-SYSTEMS VIA 2ND-ORDER AND 4TH-ORDER CUMULANT MATCHING

被引：127
作者：
TUGNAIT, JK
机构：
[1] Exxon Production Research Co,, Houston, TX, USA, Exxon Production Research Co, Houston, TX, USA
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 1987年 / 33卷 / 03期
关键词：
INFORMATION THEORY - MATHEMATICAL STATISTICS - Monte Carlo Methods - MATHEMATICAL TECHNIQUES - Correlation Methods - STATISTICAL METHODS;
D O I：
10.1109/TIT.1987.1057308
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The identification problem for 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 it is allowed to contain all-pass components. A least-squares criterion that involves matching the second- and 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 Akaike information criterion is also proposed. Strong consistency of the proposed estimator is proved under certain sufficient conditions. Simulation results are presented to illustrate the method.
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页码：393 / 407
页数：15
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