Results 251 to 260 of about 117,319,651 (289)

Identification of multivariable errors-in-variables models

1999 European Control Conference (ECC), 1999
The paper deals with a new identification approach, based on a prediction error method, for multivariable errors-in-variables models (EIV). Starting from the ARMAX decomposition of MIMO EIV processes and congruence conditions between noisy sequences and the constraints of EIV representations, the simultaneous estimate of the model parameters and of the
Paolo Castaldi, Roberto Diversi, Roberto Guidorzi, Umberto Soverini   +3 more
openaire   +1 more source

Identification of multivariable errors in variable models with dynamics

IEEE Transactions on Automatic Control, 1986
This paper extends to the multivariable case the results presented for scalar systems by the second author [Automatica 21, 709-716 (1985)]. The problem considered is that of identifying a causal, linear, dynamic multivariable system from measurements of the input and output signals corrupted by noises of unknown spectra. To solve this so-called errors-
Green, Michael, Anderson, Brian D. O.
openaire   +1 more source

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Communications in Statistics - Simulation and Computation, 2009
Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated,
Cibele M. Russo, Reiko Aoki, Dorival Leao Pinto Junior   +2 more
openaire   +1 more source

Frisch scheme–based identification of multivariable errors–in–variables models

IFAC Proceedings Volumes, 2009
Abstract This paper describes an identification procedure for minimally parametrized multivariable models in the Errors–in–Variables (EIV) context of the Frisch scheme that considers additive white observation noise on the process inputs and outputs.
DIVERSI, ROBERTO, GUIDORZI, ROBERTO
openaire   +2 more sources

Subspace algorithms for the identification of multivariable dynamic errors-in-variables models

Autom., 1997
This paper deals with the problem of identifying multivariable finite dimensional linear time-invariant systems from noisy input/output measurements. A solution is obtained by means of subspace identification algorithms. Some SMI algorithms that consistently estimate state space models are presented.
Chun Tung Chou, Michel Verhaegen
openaire   +2 more sources

Bayesian Analysis of a Multivariate Null Intercept Errors-in-Variables Regression Model

Journal of Biopharmaceutical Statistics, 2003
Longitudinal data are of great interest in analysis of clinical trials. In many practical situations the covariate can not be measured precisely and a natural alternative model is the errors-in-variables regression models. In this paper we study a null intercept errors-in-variables regression model with a structure of dependency between the response ...
Reiko, Aoki, Heleno, Bolfarine, Jorge A, Achcar, Leão P Júnior, Dorival   +3 more
openaire   +2 more sources

Subspace-based methods for the identification of multivariable dynamic errors-in-variables models

Proceedings of 35th IEEE Conference on Decision and Control, 2002
This paper analyses a multivariable errors-in-variables problem under rather general noise assumptions. Apart from the fact that both the measured input and output are corrupted by additive white noise, the output is also contaminated by a term which is caused by a white input process noise.
C.T. Chou, M.H. Verhaegen
openaire   +1 more source

Identifiability in Multivariate Dynamic Linear Errors-in-Variables Models

Journal of the American Statistical Association, 1992
Abstract This article considers multivariate causal transfer function systems with latent stationary inputs and outputs. Their observation is assumed to be disturbed by errors in variables (EV). The main identification results for such models so far consist of structure theory.
openaire   +1 more source

Closed-loop subspace identification of multivariable dynamic errors-in-variables models based on ORT

Cluster Computing, 2018
In terms of the model of errors-in-variables, this article analyses the causes of deviation based on the existing method of subspace identification in the closed-loop system; then, it puts forward another method of subspace identification with an auxiliary variable based on orthogonal decomposition.
Minghong She, Baocang Ding
openaire   +2 more sources

The identification of multivariate linear dynamic errors-in-variables models

Journal of Econometrics, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources