Add to ORKGThe problem of the estimation of the parameters of linear systems from noisy inputoutput measurements is considered. A third-order cumulant matching recursive algorithm is developed. The algorithm provides unbiased estimates of the parameters for a wide class of correlated noise corrupting both the input and the output measurements. A Monte Carlo type of simulation shows the consistency, and the superiority of the developed algorithm over the least-squares techniqu
Abstract—This paper focuses on the extension of the asymptotic covariance of the sample covariance (...
This paper studies identification problems of two-input single-output controlled autoregressive movi...
Non-linearity detection in dynamic systems is a fundamental issue in non-linear system identificatio...
The problem of the estimation of the parameters of linear systems from noisy inputoutput measurement...
The parameter estimation problem of linear systems from input output measurements, corrupted with no...
When both input and output data are contaminated by non-skewed and~or correlated (perhaps colored) G...
In this paper we develop a new linear approach to identify the parameters of a moving average (MA) m...
This paper studies the computational efficiency of the bias-eliminated least-squares (BELS) method r...
none2noAbstract: The identification of Errors-in-variables (EIV) models refers to systems where the ...
We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel wi...
It is well known that the Kalman filter is the recursive linear minimum mean-square error (LMMSE) fi...
A general linear approach to identifying the parameters of a moving average (MA) model from the stat...
A model is proposed to identify the parameters of a class of stochastic nonlinearsystems. The model ...
The covariances of the third- and fourth-order sample cumulants of stationary processes are derived....
Abstract—In this paper, we address the problem of identifying the parameters of the nonminimum-phase...
Abstract—This paper focuses on the extension of the asymptotic covariance of the sample covariance (...
This paper studies identification problems of two-input single-output controlled autoregressive movi...
Non-linearity detection in dynamic systems is a fundamental issue in non-linear system identificatio...
The problem of the estimation of the parameters of linear systems from noisy inputoutput measurement...
The parameter estimation problem of linear systems from input output measurements, corrupted with no...
When both input and output data are contaminated by non-skewed and~or correlated (perhaps colored) G...
In this paper we develop a new linear approach to identify the parameters of a moving average (MA) m...
This paper studies the computational efficiency of the bias-eliminated least-squares (BELS) method r...
none2noAbstract: The identification of Errors-in-variables (EIV) models refers to systems where the ...
We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel wi...
It is well known that the Kalman filter is the recursive linear minimum mean-square error (LMMSE) fi...
A general linear approach to identifying the parameters of a moving average (MA) model from the stat...
A model is proposed to identify the parameters of a class of stochastic nonlinearsystems. The model ...
The covariances of the third- and fourth-order sample cumulants of stationary processes are derived....
Abstract—In this paper, we address the problem of identifying the parameters of the nonminimum-phase...
Abstract—This paper focuses on the extension of the asymptotic covariance of the sample covariance (...
This paper studies identification problems of two-input single-output controlled autoregressive movi...
Non-linearity detection in dynamic systems is a fundamental issue in non-linear system identificatio...