RESEARCH ARTICLE Parameter Consistency and Quadratically Constrained Errors-in-Variables Least-Squares Identification
نویسندگان
چکیده
In this paper we investigate the consistency of parameter estimates obtained from least squares identification with a quadratic parameter constraint. For generality, we consider infinite impulse response systems with colored input and output noise. In the case of finite data, we show that there always exists a possibly indefinite quadratic constraint depending on the noise realization that yields the true parameters of the system when a persistency condition is satisfied. When the autocorrelation matrix of the output noise is known to within a scalar multiple, we show that the quadratically constrained least squares estimator with a semidefinite constraint matrix yields consistent parameter estimates.
منابع مشابه
Parameter consistency and quadratically constrained errors-in-variables least-squares identification
In this article, we investigate the consistency of parameter estimates obtained from least-squares identification with a quadratic parameter constraint. For generality, we consider infinite impulse-response systems with coloured input and output noise. In the case of finite data, we show that there always exists a possibly indefinite quadratic constraint depending on the noise realisation that ...
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