Suchergebnisse - pseudo-linear regression algorithms
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Some remarks on the bias distribution analysis of discrete-time identification algorithms based on pseudo-linear regressions
ISSN: 0167-6911, 1872-7956Veröffentlicht: Elsevier B.V 01.09.2018Veröffentlicht in Systems & control letters (01.09.2018)“… ), not for pseudo-linear regression (PLR) ones, for which we give the correct frequency domain bias analysis, both in open- and closed-loop …”
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On the convergence of pseudo-linear regression algorithms
ISSN: 0020-7179, 1366-5820Veröffentlicht: London Taylor & Francis Group 01.01.1985Veröffentlicht in International journal of control (01.01.1985)“… The convergence properties of a general iterative (off-line) pseudo-linear regression (PLR …”
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On the asymptotic accuracy of pseudo-linear regression algorithms
ISSN: 0020-7179, 1366-5820Veröffentlicht: London Taylor & Francis Group 01.01.1984Veröffentlicht in International journal of control (01.01.1984)“… The accuracy properties of a general pseudo-linear regression (PLR) method are examined …”
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Existence of stationary points for pseudo-linear regression identification algorithms
ISSN: 0018-9286Veröffentlicht: New York, NY IEEE 01.05.1999Veröffentlicht in IEEE transactions on automatic control (01.05.1999)“… The authors prove the existence of a stable transfer function satisfying the nonlinear equations characterizing an asymptotic stationary point, in undermodeled cases, for a class of pseudo-linear …”
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Some remarks on the bias distribution analysis of discrete-time identification algorithms based on pseudo-linear regressions
ISSN: 2331-8422Veröffentlicht: Ithaca Cornell University Library, arXiv.org 18.06.2018Veröffentlicht in arXiv.org (18.06.2018)“… ), not for pseudo-linear regression (PLR) ones, for which we give the correct frequency domain bias analysis, both in open- and closed-loop …”
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Gradient-based iterative parameter estimation for Box–Jenkins systems
ISSN: 0898-1221, 1873-7668Veröffentlicht: Elsevier Ltd 01.09.2010Veröffentlicht in Computers & mathematics with applications (1987) (01.09.2010)“… –Jenkins systems with finite measurement input/output data. Compared with the pseudo-linear regression stochastic gradient approach, the proposed algorithm updates …”
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Identification for Precision Mechatronics: An Auxiliary Model‐Based Hierarchical Refined Instrumental Variable Algorithm
ISSN: 1049-8923, 1099-1239Veröffentlicht: Hoboken, USA John Wiley & Sons, Inc 01.08.2025Veröffentlicht in International journal of robust and nonlinear control (01.08.2025)“… Based on the maximum likelihood principle, the optimality conditions for the proposed identification algorithms are formulated for ACTARMA systems …”
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Convergence of the recursive identification algorithms for multivariate pseudo-linear regressive systems
ISSN: 0890-6327, 1099-1115Veröffentlicht: Bognor Regis Blackwell Publishing Ltd 01.06.2016Veröffentlicht in International journal of adaptive control and signal processing (01.06.2016)“… stochastic gradient algorithm, for pseudo‐linear multivariate systems and proves that the parameter estimation errors consistently converge to zero under persistent excitation conditions …”
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Multiinnovation Least-Squares Identification for System Modeling
ISSN: 1083-4419, 1941-0492, 1941-0492Veröffentlicht: United States IEEE 01.06.2010Veröffentlicht in IEEE transactions on systems, man and cybernetics. Part B, Cybernetics (01.06.2010)“… A multiinnovation least-squares (MILS) identification algorithm is presented for linear regression models with unknown parameter vectors by expanding the innovation length in the traditional recursive least-squares (RLS …”
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Improved-RSSI-based indoor localization by using pseudo-linear solution with machine learning algorithms
ISSN: 2314-7172, 2314-7172Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024Veröffentlicht in Journal of Electrical Systems and Information Technology (01.12.2024)“… Therefore, this study proposes a machine learning (ML)-based improved RSSI-based indoor localization approach in which RSSI data is first augmented and then classified using ML algorithms …”
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Recursive computational formulas of the least squares criterion functions for scalar system identification
ISSN: 0307-904XVeröffentlicht: Elsevier Inc 01.01.2014Veröffentlicht in Applied mathematical modelling (01.01.2014)“… The proposed recursive computation formulas can be extended to the estimation algorithms of the pseudo-linear regression models for equation error systems and output error systems …”
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A New Absolute Encoder Design Based on Piecewise Pseudo-Linear Signals
ISSN: 1530-437X, 1558-1748Veröffentlicht: New York IEEE 15.08.2024Veröffentlicht in IEEE sensors journal (15.08.2024)“… by conventional sine-cosine encoders. The obtained pseudo-linear sections are made more linear through third-order polynomial regression …”
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Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach
ISSN: 2169-3536, 2169-3536Veröffentlicht: Piscataway IEEE 2020Veröffentlicht in IEEE access (2020)“… Interest in the study of next-generation underwater sensor networks for ocean investigations has increased owing to developing concerns over their utilization …”
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An l2-stable feedback structure for nonlinear adaptive filtering and identification
ISSN: 0005-1098, 1873-2836Veröffentlicht: Oxford Elsevier Ltd 1997Veröffentlicht in Automatica (Oxford) (1997)“… in IIR modeling and more recent results in H ∞ theory. In particular, two algorithms due to Feintuch and to Landau, as well as the so-called pseudo-linear regression and Gauss-Newton algorithms, are discussed within the framework proposed here …”
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Pseudo-linear regression identification based on generalized orthonormal transfer functions: Convergence conditions and bias distribution
ISSN: 2331-8422Veröffentlicht: Ithaca Cornell University Library, arXiv.org 13.08.2019Veröffentlicht in arXiv.org (13.08.2019)“… This result is specific to pseudo-linear regression properties, and cannot be transposed to most of prediction error method algorithms …”
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Acoustic echo cancelation using a pseudo-linear regression and QR-decomposition
ISBN: 9780780330733, 0780330730Veröffentlicht: IEEE 1996Veröffentlicht in 1996 IEEE International Symposium on Circuits and Systems (1996)“… In this paper the problem of acoustic echo cancelation is addressed using an adaptive IIR filtering algorithm based on a QR decomposition and a pseudo-linear regression …”
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Adaptive IIR filtering using QR matrix decomposition
ISSN: 1053-587XVeröffentlicht: New York, NY IEEE 01.09.1998Veröffentlicht in IEEE transactions on signal processing (01.09.1998)“… In this correspondence, an approach to adaptive IIR filtering based on a pseudo-linear regression and applying an iterative QR matrix decomposition is developed …”
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A new algorithm for state estimation of stochastic linear discrete systems
ISSN: 0018-9286Veröffentlicht: New York, NY IEEE 01.08.1994Veröffentlicht in IEEE transactions on automatic control (01.08.1994)“… The procedure performs explicit minimization of the innovation variance and is based upon the principle of pseudo linear regression (PLR) method …”
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New approach for kinetic parameters determination for hydrothermal oxidation reaction
ISSN: 0896-8446, 1872-8162Veröffentlicht: Elsevier B.V 01.05.2005Veröffentlicht in The Journal of supercritical fluids (01.05.2005)“… °C and at a constant pressure of 25 MPa. Three different methods, namely pseudo-first-order kinetics, multiple linear regression and Runge …”
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Artificial neural network models for fault detection and isolation of industrial processes
ISSN: 2299-3649, 2956-5839Veröffentlicht: Institute of Fundamental Technological Research Polish Academy of Sciences 01.02.2023Veröffentlicht in Computer assisted methods in engineering and science (01.02.2023)“… The paper focuses on using of artificial neural networks in model-based fault detection and isolation. Modelling of a system both at its normal operation …”
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