| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A concave approach to errors-in-variables sparse linear system identification
|
Fosson, S.M.
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|
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54 |
7 |
p. 298-303
|
artikel
|
| 2 |
Adaptive Closed-Loop Identification and Tracking Control of an Aerial Vehicle with Unknown Inertia Parameters ⁎ ⁎ The work is supported by the Engineering and Physical Sciences Research Council (EPSRC), grant number EP/R02572X/1, and National Centre for Nuclear Robotics.
|
Imran, Imil Hamda
|
|
|
54 |
7 |
p. 785-790
|
artikel
|
| 3 |
Adaptive dynamic predictive monitoring scheme based on DLV models
|
Dong, Yining
|
|
|
54 |
7 |
p. 91-96
|
artikel
|
| 4 |
Adaptive Observer for Systems with Distributed Output Delay
|
Lailler, Manon
|
|
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54 |
7 |
p. 120-125
|
artikel
|
| 5 |
A Frequency Domain Approach to Model Reference Control
|
Marc, Berneman
|
|
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54 |
7 |
p. 216-221
|
artikel
|
| 6 |
A Friction Model based on Parallelization of Original LuGre Models and the Corresponding Compensator
|
Pouilly-Cathelain, M.
|
|
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54 |
7 |
p. 499-504
|
artikel
|
| 7 |
A Generalized Multidimensional Circulant Rational Covariance and Cepstral Extension Problem ⁎ ⁎ This work was supported by the SID project “A Multidimensional and Multivariate Moment Problem Theory for Target Parameter Estimation in Automotive Radars” (ZORZ_SID19_01) funded by the Department of Information Engineering of the University of Padova. B. Zhu was also partially supported by the “Hundred-Talent Program” of the Sun Yat-sen University.
|
Zhu, Bin
|
|
|
54 |
7 |
p. 553-558
|
artikel
|
| 8 |
Algorithms for Block Tridiagonal Systems: Stability Results for Generalized Kalman Smoothing
|
Aravkin, Aleksandr Y.
|
|
|
54 |
7 |
p. 821-826
|
artikel
|
| 9 |
A Möbius Transform Approach for Improved MIMO Frequency Domain Identification ⁎ ⁎ This research has been carried out in the ChaseOn Centre in a project financed by Vinnova, Chalmers, Food Radar Systems, Keysight Technologies, Medfield Diagnostics, Saab and UniqueSec
|
McKelvey, T.
|
|
|
54 |
7 |
p. 791-796
|
artikel
|
| 10 |
A Multivariate Local Rational Modeling Approach for Detection of Structural Changes in Test Vehicles ⁎ ⁎ This work has been performed within FFI project ETAVEP with support from Vinnova and Volvo Cars.
|
McKelvey, T.
|
|
|
54 |
7 |
p. 79-84
|
artikel
|
| 11 |
An Actor-Critic approach for control of Residential Photovoltaic-Battery Systems
|
Joshi, Amit
|
|
|
54 |
7 |
p. 222-227
|
artikel
|
| 12 |
An efficient network reconstruction method and applications
|
Dimovska, Mihaela
|
|
|
54 |
7 |
p. 49-54
|
artikel
|
| 13 |
An empirical study on decoupling PNLSS models illustrated on an airplane
|
Csurcsia, Péter Zoltán
|
|
|
54 |
7 |
p. 673-678
|
artikel
|
| 14 |
A new Graphical User Interface for the CONTSID toolbox for Matlab
|
Garnier, H.
|
|
|
54 |
7 |
p. 397-402
|
artikel
|
| 15 |
A new scheme for fault detection based on Optimal Upper Bounded Interval Kalman Filter
|
Lu, Quoc Hung
|
|
|
54 |
7 |
p. 292-297
|
artikel
|
| 16 |
An Introduction of a CCA Weighting Matrix to a Closed-Loop Subspace Identification Method
|
Ikeda, Kenji
|
|
|
54 |
7 |
p. 761-766
|
artikel
|
| 17 |
An LTV Approach to Identifying Nonlinear Systems-with Application to an RRR-Robot 1 1 This research was funded by the Research Foundation Flanders (FWO-Vlaanderen) and the Flemish Government (Methusalem Fund METH1). This work is part of the research programme VIDI with project number 15698, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO).
|
Lataire, John
|
|
|
54 |
7 |
p. 445-450
|
artikel
|
| 18 |
Anomaly detection via distributed sensing: a VAR modeling approach
|
Abbracciavento, Francesco
|
|
|
54 |
7 |
p. 85-90
|
artikel
|
| 19 |
A novel Deep Neural Network architecture for non-linear system identification ⁎ ⁎ This project was partially supported by the Italian Ministry of University and Research under the PRIN’17 project ”Data-driven learning of constrained control systems”, contract no. 2017J89ARP and by NVIDIA Corporation trough the GPU Grant Program.
|
Zancato, Luca
|
|
|
54 |
7 |
p. 186-191
|
artikel
|
| 20 |
A Novel Thick Ellipsoid Approach for Verified Outer and Inner State Enclosures of Discrete-Time Dynamic Systems
|
Rauh, Andreas
|
|
|
54 |
7 |
p. 601-606
|
artikel
|
| 21 |
Approaches for green roof dynamic model analysis using GSA
|
Hégo, A.
|
|
|
54 |
7 |
p. 613-618
|
artikel
|
| 22 |
Approximate Piecewise Affine Decomposition of Neural Networks
|
Robinson, Haakon
|
|
|
54 |
7 |
p. 541-546
|
artikel
|
| 23 |
A pseudo-linear regression algorithm in discrete-time for the efficient identification of stiff systems
|
Vau, Bernard
|
|
|
54 |
7 |
p. 322-327
|
artikel
|
| 24 |
Artificial Neural Network Hysteresis Operators for the Identification of Hammerstein Hysteretic Systems
|
Krikelis, Konstantinos
|
|
|
54 |
7 |
p. 702-707
|
artikel
|
| 25 |
A Simulation-induced Regularization Method for System Identification ⁎ ⁎ This work was supported by the Thousand Youth Talents Plan funded by the central government of China, the general project funded by NSFC under contract No. 61773329, the Shenzhen research projects funded by the Shenzhen Science and Technology Innovation Council under contract No. Ji-20170189, the President’s grant under contract No. PF. 01.000249 and the Start-up grant under contract No. 2014.0003.23 funded by CUHKSZ.
|
Chen, Tianshi
|
|
|
54 |
7 |
p. 726-731
|
artikel
|
| 26 |
Bayes Control of Hammerstein Systems
|
Ferizbegovic, Mina
|
|
|
54 |
7 |
p. 755-760
|
artikel
|
| 27 |
Bayesian Frequency Estimation on Narrow Bands ⁎ ⁎ B. Zhu was supported by the “Hundred-Talent Program” of the Sun Yat-sen University.
|
Picci, Giorgio
|
|
|
54 |
7 |
p. 108-113
|
artikel
|
| 28 |
Bayesian optimization for Tuning Lithography Processes
|
Guler, Sila
|
|
|
54 |
7 |
p. 827-832
|
artikel
|
| 29 |
Beyond Occam’s Razor in System Identification: Double-Descent when Modeling Dynamics
|
Ribeiro, Antônio H.
|
|
|
54 |
7 |
p. 97-102
|
artikel
|
| 30 |
Boundedness of the Kalman Filter Revisited
|
Zhang, Qinghua
|
|
|
54 |
7 |
p. 334-338
|
artikel
|
| 31 |
Combined state and parameter estimation for a landslide model using Kalman filter
|
Mishra, Mohit
|
|
|
54 |
7 |
p. 304-309
|
artikel
|
| 32 |
Common dynamic estimation via structured low-rank approximation with multiple rank constraints
|
Fazzi, Antonio
|
|
|
54 |
7 |
p. 103-107
|
artikel
|
| 33 |
Comparison of Least-Squares and Instrumental Variables for Parameters Estimation on Differential Drive Mobile Robots
|
Ardiani, Fabio
|
|
|
54 |
7 |
p. 310-315
|
artikel
|
| 34 |
Computing Measures of Identifiability, Observability, and Controllability for a Dynamic System Model with the StrucID App
|
Stigter, J.D.
|
|
|
54 |
7 |
p. 138-143
|
artikel
|
| 35 |
Constrained learning for model predictive control in asymptotically constant reference tracking tasks
|
Matschek, Janine
|
|
|
54 |
7 |
p. 244-249
|
artikel
|
| 36 |
Contents
|
|
|
|
54 |
7 |
p. i-vii
|
artikel
|
| 37 |
Convergence Analysis of Weighted SPSA-based Consensus Algorithm in Distributed Parameter Estimation Problem
|
Sergeenko, Anna
|
|
|
54 |
7 |
p. 126-131
|
artikel
|
| 38 |
Cooperative System Identification via Correctional Learning ⁎ ⁎ This work was supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP), the Swedish Research Council and the Swedish Research Council Research Environment NewLEADS under contract 2016-06079.
|
Lourenço, Inês
|
|
|
54 |
7 |
p. 19-24
|
artikel
|
| 39 |
Correcting esophageal pressure measurements for patients undergoing mechanical ventilation
|
Wang Xia, Yu Hao
|
|
|
54 |
7 |
p. 156-161
|
artikel
|
| 40 |
Damage Localization in Mechanical Systems by Lasso Regression
|
Döhler, Michael
|
|
|
54 |
7 |
p. 286-291
|
artikel
|
| 41 |
Data-Based Model of an Omnidirectional Mobile Robot Using Gaussian Processes
|
Eschmann, Hannes
|
|
|
54 |
7 |
p. 13-18
|
artikel
|
| 42 |
Data-driven analysis and control of continuous-time systems under aperiodic sampling ⁎ ⁎ This work was funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 -390740016 and under grant AL 316/13-2 - 285825138. We acknowledge the support by the Stuttgart Center for Simulation Science (SimTech). The authors thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Julian Berberich.
|
Berberich, Julian
|
|
|
54 |
7 |
p. 210-215
|
artikel
|
| 43 |
Data-Driven Input-Passivity Estimation Using Power Iterations
|
Müller, Matias I.
|
|
|
54 |
7 |
p. 619-624
|
artikel
|
| 44 |
Data-Driven LPV Controller Design for Islanded Microgrids ⁎ ⁎ This project is carried out within the frame of the Swiss Centre for Competence in Energy Research on the Future Swiss Electrical Infrastructure (SCCER-FURIES) with the financial support of the Swiss Innovation Agency (Innosuisse - SCCER program). The work of S. S. Madani is supported by the Swiss National Science Foundation under Grant 200021_172828.
|
Madani, Seyed Sohail
|
|
|
54 |
7 |
p. 433-438
|
artikel
|
| 45 |
Data-driven System Identification of Thermal Systems using Machine Learning
|
Nechita, Ştefan-Cristian
|
|
|
54 |
7 |
p. 162-167
|
artikel
|
| 46 |
Data Informativity for the Closed-Loop Identification of MISO ARX Systems
|
Colin, Kévin
|
|
|
54 |
7 |
p. 779-784
|
artikel
|
| 47 |
Decoupling multivariate functions using a non-parametric Filtered CPD approach ⁎ ⁎ This work was supported by the Flemish fund for scientific research FWO under license number G0068.18N.
|
Decuyper, Jan
|
|
|
54 |
7 |
p. 451-456
|
artikel
|
| 48 |
Decoupling Non-Polynomial Functions: A Neural Network Example ⁎ ⁎ Supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) through grant RGPIN/06464-2015 and the Fund for Scientific Research (FWO- Vlaanderen), by the ERC Advanced Grant SNLSID under contract 320378 and by FWO project G.0280.15N.
|
Westwick, David T.
|
|
|
54 |
7 |
p. 667-672
|
artikel
|
| 49 |
Decoupling P-NARX models using filtered CPD
|
Decuyper, Jan
|
|
|
54 |
7 |
p. 661-666
|
artikel
|
| 50 |
Deep Energy-Based NARX Models ⁎ ⁎ This research was financially supported by the projects Learning flexible models for nonlinear dynamics (contract number: 2017-03807), NewLEADS - New Directions in Learning Dynamical Systems (contract number: 621-2016-06079), by the Swedish Research Council, by the Brazilian research agency CAPES and by Kjell och Marta Beijer Foundation.
|
Hendriks, Johannes N.
|
|
|
54 |
7 |
p. 505-510
|
artikel
|
| 51 |
Deep Learning For Fault Detection In Transformers Using Vibration Data
|
Rucconi, V.
|
|
|
54 |
7 |
p. 262-267
|
artikel
|
| 52 |
Deep learning with transfer functions: new applications in system identification ⁎ ⁎ This work was partially supported by the European H2020-CS2 project ADMITTED, Grant agreement no. GA832003.
|
Piga, Dario
|
|
|
54 |
7 |
p. 415-420
|
artikel
|
| 53 |
Deep State Space Models for Nonlinear System Identification ⁎ ⁎ This research was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation and the Swedish Research Council, contracts 2016-06079 and 2019-04956.
|
Gedon, Daniel
|
|
|
54 |
7 |
p. 481-486
|
artikel
|
| 54 |
Detection of Glucose Sensor Faults in an Artificial Pancreas via Whiteness Test on Kalman Filter Residuals
|
Manzoni, Eleonora
|
|
|
54 |
7 |
p. 274-279
|
artikel
|
| 55 |
Dynamic Autoregressive Partial Least Squares for Supervised Modeling
|
Zhu, Qinqin
|
|
|
54 |
7 |
p. 234-239
|
artikel
|
| 56 |
Efficient Implementation of Kernel Regularization based on ADMM
|
Fujimoto, Yusuke
|
|
|
54 |
7 |
p. 744-748
|
artikel
|
| 57 |
Elastic Shape Analysis for Anomaly Detection in Fabric Images
|
Ferro, Fabiana Federica
|
|
|
54 |
7 |
p. 67-72
|
artikel
|
| 58 |
Enforcing symmetry in tensor network MIMO Volterra identification
|
Batselier, Kim
|
|
|
54 |
7 |
p. 469-474
|
artikel
|
| 59 |
Estimating Koopman operators for nonlinear dynamical systems: a nonparametric approach
|
Zanini, Francesco
|
|
|
54 |
7 |
p. 691-696
|
artikel
|
| 60 |
Experiment design for impulse response identification with signal matrix models ⁎ ⁎ This work is supported by the Swiss National Science Foundation under grant no. 200021_178890.
|
Iannelli, Andrea
|
|
|
54 |
7 |
p. 625-630
|
artikel
|
| 61 |
Extrapolation Behavior Comparison of Nonlinear State Space Models
|
Schüssler, Max
|
|
|
54 |
7 |
p. 487-492
|
artikel
|
| 62 |
Frequency-domain identification of stereoelectroencephalographic transfer functions for brain tissue classification
|
Pinheiro Machado, Mariana Mulinari
|
|
|
54 |
7 |
p. 565-570
|
artikel
|
| 63 |
FSID - A Frequency Weighted MIMO Frequency Domain Identification and Rational Matrix Approximation Method for Python, Julia and Matlab
|
McKelvey, T.
|
|
|
54 |
7 |
p. 403-408
|
artikel
|
| 64 |
Handling unmeasured disturbances in data-driven distributed control with virtual reference feedback tuning ⁎ ⁎ Funded by the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Unions Horizon 2020 research and innovation programme (grant agreement N0 694504).
|
Steentjes, Tom R.V.
|
|
|
54 |
7 |
p. 204-209
|
artikel
|
| 65 |
Hankel matrix-based Mahalanobis distance for fault detection robust towards changes in process noise covariance
|
Greś, Szymon
|
|
|
54 |
7 |
p. 73-78
|
artikel
|
| 66 |
How Statistical Learning Can Help to Estimate the Number of Modes in Switched System Identification?
|
Massucci, Louis
|
|
|
54 |
7 |
p. 637-642
|
artikel
|
| 67 |
Identifiability of Dynamic Networks from Structure
|
Mapurunga, Eduardo
|
|
|
54 |
7 |
p. 55-60
|
artikel
|
| 68 |
Identifiability of linear dynamic networks through switching modules ⁎ ⁎ This project has received funding from the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 694504).
|
Dreef, H.J.
|
|
|
54 |
7 |
p. 37-42
|
artikel
|
| 69 |
Identifiability of Unique Elements of Noise Covariances in State-Space Models
|
Kost, Oliver
|
|
|
54 |
7 |
p. 316-321
|
artikel
|
| 70 |
Identification and comparison of two nonlinear extended phenomenological models for an automotive ElectroRheological (ER) damper
|
Priyatharrshan, S.K.
|
|
|
54 |
7 |
p. 439-444
|
artikel
|
| 71 |
Identification of a cell population model for algae growth processes ⁎ ⁎ This project has been supported by the Deutsche Forschungsge-meinschaft (DFG) with Grant number 395461267 and by Erasmus+ that has provided Federico Atzori with a scholarship for the internship at the Chair of Automatic Control at Kiel University
|
Atzori, F.
|
|
|
54 |
7 |
p. 132-137
|
artikel
|
| 72 |
Identification of Continuous-time Linear Time-varying Systems with Abrupt Changes in Parameters ⁎ ⁎ This work was supported by the Australian government Research Training Program (RTP) scholarship
|
Pan, Siqi
|
|
|
54 |
7 |
p. 339-344
|
artikel
|
| 73 |
Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
|
Niedźwiecki, Maciej
|
|
|
54 |
7 |
p. 351-356
|
artikel
|
| 74 |
Identification of Output-Error Models and an Iterative Optimization Algorithm to Size Fast Ancillary Services for Grid Frequency Control ⁎ ⁎ This work has been financed by the Research Fund for the Italian power system in compliance with the Decree of Minister of Economic Development April 16, 2018.
|
Rapizza, Marco R.
|
|
|
54 |
7 |
p. 25-30
|
artikel
|
| 75 |
Identification of stochastic gene expression models over lineage trees
|
Marguet, Aline
|
|
|
54 |
7 |
p. 150-155
|
artikel
|
| 76 |
Identification of the nonlinear steering dynamics of an autonomous vehicle ⁎ ⁎ The research presented in this paper was carried out as part of the “Dynamics and Control of Autonomous Vehicles meeting the Synergy Demands of Automated Transport Systems (EFOP-3.6.2-16-2017-00016)” project in the framework of the New Szechenyi Plan. The research was also supported by the Ministry of Innovation and Technology NRDI Office within the framework of the Autonomous Systems National Laboratory Program
|
Rödönyi, G.
|
|
|
54 |
7 |
p. 708-713
|
artikel
|
| 77 |
Improved frequency response function estimation by Gaussian process regression with prior knowledge ⁎ ⁎ This research was supported in part by the Fund for Scientific Research (FWO Vlaanderen), and in part by the Flemish Government (Methusalem Grant METH1).
|
Hallemans, N.
|
|
|
54 |
7 |
p. 559-564
|
artikel
|
| 78 |
Information Optimal Control for Single Particle Tracking Microscopy
|
Vickers, Nicholas A.
|
|
|
54 |
7 |
p. 649-654
|
artikel
|
| 79 |
Integrated theoretical and data-driven Gaussian Process NARX Model for the Simulation of Effluent Concentrations in Wastewater Treatment Plant ⁎ ⁎ The authors acknowledge the research core funding No. P2-0001, and Ph.D. grant for Tadej Krivec which were financially supported by the Slovenian Research Agency.
|
Krivec, Tadej
|
|
|
54 |
7 |
p. 714-719
|
artikel
|
| 80 |
Joint Estimation of Trajectory and Model Parameters for Single Particle Tracking of 3D Confined Diffusion Using the Double-Helix Point Spread Function ⁎ ⁎ This work was supported in part by NIH through 1R01GM117039-01A1.
|
Lin, Ye
|
|
|
54 |
7 |
p. 511-516
|
artikel
|
| 81 |
Kernel-based Regularized Iterative Learning Control of Repetitive Linear Time-varying Systems ⁎ ⁎ Yu’s and Chen’s contribution to this work was supported by the Thousand Youth Talents Plan funded by the central government of China, the general project funded by NSFC under contract No. 61773329, the Shenzhen research projects funded by the Shenzhen Science and Technology Innovation Council under contract No. Ji-20170189, the President’s grant under contract No. PF. 01.000249 and the Start-up grant under contract No. 2014.0003.23 funded by CUHKSZ. Mu’s contribution to this work was supported (in part) by the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No. XDA27000000. Ljung’s contribution to this work was supported by the Swedish Research Council, contract 2019-04956 and by Vinnova’s center LINKSIC.
|
Yu, Xian
|
|
|
54 |
7 |
p. 738-743
|
artikel
|
| 82 |
Learning deep autoregressive models for hierarchical data
|
Andersson, Carl R.
|
|
|
54 |
7 |
p. 529-534
|
artikel
|
| 83 |
Learning Models of Model Predictive Controllers using Gradient Data ⁎ ⁎ This work was partially supported by the Swedish Research Council and by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation and the Swedish Research Council Research Environment NewLEADS under contract 2016-06079.
|
Winqvist, Rebecka
|
|
|
54 |
7 |
p. 7-12
|
artikel
|
| 84 |
Learning nonlinearities in the decoupling problem with structured CPD
|
Zniyed, Yassine
|
|
|
54 |
7 |
p. 685-690
|
artikel
|
| 85 |
Learning to Model the Grasp Space of an Underactuated Robot Gripper Using Variational Autoencoder
|
Rolinat, Clément
|
|
|
54 |
7 |
p. 523-528
|
artikel
|
| 86 |
Low-rank tensor recovery for Jacobian-based Volterra identification of parallel Wiener-Hammerstein systems
|
Usevich, Konstantin
|
|
|
54 |
7 |
p. 463-468
|
artikel
|
| 87 |
LPVcore: MATLAB Toolbox for LPV Modelling, Identification and Control
|
den Boef, Pascal
|
|
|
54 |
7 |
p. 385-390
|
artikel
|
| 88 |
Methods for Traffic Data Classification with regard to Potential Safety Hazards ⁎ ⁎ This work has been supported by the LCM K2 Center within the framework of the Austrian COMET-K2 program.
|
Obereigner, Gunda
|
|
|
54 |
7 |
p. 250-255
|
artikel
|
| 89 |
Minimal realization of an unstable plant under feedback ⁎ ⁎ This work is partly supported by JSPS KAKENHI Grant Number 20K04535.
|
Tanaka, Hideyuki
|
|
|
54 |
7 |
p. 773-778
|
artikel
|
| 90 |
Modeling and Identification of Low Rank Vector Processes
|
Picci, Giorgio
|
|
|
54 |
7 |
p. 631-636
|
artikel
|
| 91 |
Modeling and simulation of bimetallic strips in industrial circuit breakers ⁎ ⁎ The research has been carried in the SMART4CPPS (Smart Solutions for Cyber-Physical Production Systems) project funded by FESR (Fondo Europeo di Sviluppo Regionale).
|
Maurelli, L.
|
|
|
54 |
7 |
p. 803-808
|
artikel
|
| 92 |
Model Order Selection in Robust-Control-Relevant System Identification
|
Tacx, Paul
|
|
|
54 |
7 |
p. 1-6
|
artikel
|
| 93 |
Modulating Function Based Fault Diagnosis Using the Parity Space Method
|
Enciso, Luis
|
|
|
54 |
7 |
p. 268-273
|
artikel
|
| 94 |
Modulation-Function-Based Finite-Horizon Sensor Fault Detection for Salient-Pole PMSM using Parity-Space Residuals
|
Jahn, Benjamin
|
|
|
54 |
7 |
p. 61-66
|
artikel
|
| 95 |
Network topology detection via uncertainty analysis of an identified static model
|
Bombois, X.
|
|
|
54 |
7 |
p. 595-600
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| 96 |
New Features in the System Identification Toolbox - Rapprochements with Machine Learning
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Aljanaideh, Khaled F.
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p. 369-373
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artikel
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| 97 |
Non-asymptotic Confidence Regions for Errors-In-Variables Systems in an Extended Noise Environment
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Khorasani, Masoud Moravej
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p. 583-588
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artikel
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| 98 |
Nonlinear Finite Impulse Response Estimation using Regularized Neural Networks
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Ramírez-Chavarría, Roberto G.
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p. 174-179
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| 99 |
Nonlinear Mixed Effects Modeling of Deterministic and Stochastic Dynamical Systems in Wolfram Mathematica ⁎ ⁎ This work has been partly founded by the Swedish Foundation for Strategic Research by the project Hierarchical Mixed Effects Modeling of Dynamical Systems (Grant no. AM13-0046).
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Leander, Jacob
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54 |
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p. 409-414
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artikel
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| 100 |
Non-linear State-space Model Identification from Video Data using Deep Encoders
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Beintema, Gerben I.
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p. 697-701
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artikel
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| 101 |
Nonlinear System Identification with Dominating Output Noise - A Case Study on the Silverbox
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Schoukens, J.
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p. 679-684
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artikel
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| 102 |
Normalising Flows and Nonlinear Normal Modes
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Bull, L.A.
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54 |
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p. 655-660
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artikel
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| 103 |
On consistency of output-error closed-loop subspace model identification for systems compensated by general LTI controllers ⁎ ⁎ This work was supported by JSPS KAKENHI Grant Number 18K04217.
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Oku, Hiroshi
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54 |
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p. 767-772
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artikel
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| 104 |
One-bit System Identification
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Carbone, Paolo
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54 |
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p. 571-576
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artikel
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| 105 |
On Filtering Methods for State-Space Systems having Binary Output Measurements ⁎ ⁎ This work was partially supported by FONDECYT through grant No 1181158, Chilean National Agency for Research and Development (ANID) Scholarship Program/Doctorado Nacional/2020-21202410, PIIC program of DGP at Universidad Tecnica Federico Santa María No 016/2020 and the Advanced Center for Electrical and Electronic Engineering, AC3E, Basal Project FB0008, ANID, Chile.
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Cedeño, Angel L.
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p. 815-820
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artikel
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| 106 |
On Identification of Nonlinear ARX Models with Sparsity in Regressors and Basis Functions
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Singh, Rajiv
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54 |
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p. 720-725
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artikel
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| 107 |
On Low-Rank Hankel Matrix Denoising
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Yin, Mingzhou
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54 |
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p. 198-203
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artikel
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| 108 |
On recursive Markov parameters estimation for MIMO systems
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Gonçalves da Silva, Gustavo R.
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p. 357-362
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artikel
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| 109 |
On Robustness of Kernel-Based Regularized System Identification
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Khosravi, Mohammad
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p. 749-754
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artikel
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| 110 |
On the Identification of Social Cognitive Theory Models and Closed-loop Intervention Simulations Using Hybrid Model Predictive Control
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Freigoun, Mohammad T.
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p. 31-36
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artikel
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| 111 |
On the Uncertainty Modelling for Linear Continuous-Time Systems Utilising Sampled Data and Gaussian Mixture Models ⁎ ⁎ This work was supported by ANID/Doctorado Nacional/2017-21170804, ANID-FONDECYT grants 1211630 and 11201187, DPP at Universidad Técnica Federico Santa María and the Advanced Center for Electrical and Electronic Engineering, AC3E, Basal Project FB0008, ANID, Chile.
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Orellana, Rafael
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54 |
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p. 589-594
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artikel
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| 112 |
Optimal Allocation of Excitation and Measurement for Identification of Dynamic Networks ⁎ ⁎ This study was financed in part by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeicoamento de Pessoal de Nível Superior - Brasil (CAPES) -Finance Code 001.
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Mapurunga, Eduardo
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p. 43-48
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artikel
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| 113 |
Parameter Estimation of Parallel Wiener-Hammerstein Systems by Decoupling their Volterra Representations ⁎ ⁎ This research was supported by KU Leuven Research Fund; FWO (EOS Project 30468160 (SeLMA), SBO project S005319N, Infrastructure project I013218N, TBM Project T001919N, G028015N, G090117N, SB/1SA1319N, SB/1S93918, SB/151622); Flemish Government (AI Research Program); European Research Council under the European Union’s Horizon 2020 research and innovation programme (ERC AdG grant 885682), KU Leuven start-up-grant STG/19/036 ZKD7924. PD is affiliated to Leuven.AI - KU Leuven institute for AI, Leuven, Belgium. Part of this work was performed while the authors were with Dept. ELEC of Vrije Universiteit Brus-sel, and PD was with CoSys-lab at Universiteit Antwerpen, Belgium.
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Dreesen, Philippe
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54 |
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p. 457-462
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artikel
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| 114 |
Parameter identification of a yeast batch cell population balance model ⁎ ⁎ Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 395461267.
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Jerono, P.
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54 |
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p. 144-149
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artikel
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| 115 |
Parametric Identification of a Linear Time Invariant Model for a Subglottal System ⁎ ⁎ This work was supported by the Advanced Center for Electrical and Electronic Engineering, AC3E, Basal Project FB0008, ANID; and the National Institutes of Health (NIH) National Institute on Deafness and Other Communication Disorders through Grant P50DC015446. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
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Fontanet, Javier G.
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p. 577-582
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artikel
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| 116 |
Physics-derived covariance functions for machine learning in structural dynamics ⁎ ⁎ The authors would like to acknowledge the support of the EPSRC, particularly through grant reference number EP/S001565/1
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Cross, Elizabeth J.
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54 |
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p. 168-173
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artikel
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| 117 |
Physics Informed Stochastic Grey-Box Model of the Flow-Front in a Vacuum Assisted Resin Transfer Moulding Process with Missing Data
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Relan, Rishi
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54 |
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p. 797-802
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artikel
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| 118 |
Piecewise nonlinear regression with data augmentation
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Mazzoleni, M.
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54 |
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p. 421-426
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artikel
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| 119 |
Piecewise Polynomial Model Identification using Constrained Least Squares for UAS Stall
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Guibert, Vincent
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54 |
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p. 493-498
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artikel
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| 120 |
PNLSS Toolbox 1.0 ⁎ ⁎ This work was supported by the Flemish fund for scientific research FWO under license number G0068.18N.
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Decuyper, Jan
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54 |
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p. 374-378
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artikel
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| 121 |
Prognosis based on the Joint Parameter/State Estimation Using Zonotopic LPV Set-Membership Approach ⁎ ⁎ This work is partially funded by the Catalan Agency for Management of University and Research Grants (AGAUR) and the European Social Fund (ESF) of the Government of Catalonia through the grant FI-SDUR-AGAUR 2020 (ref. 2020-FISDU-307). It is also partially funded by European Union and Normandy Region. Europe is involved in Normandy through the European Funds for Regional Development.
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Al-Mohamad, Ahmad
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p. 280-285
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artikel
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| 122 |
Quadratic Regularization of Data-Enabled Predictive Control: Theory and Application to Power Converter Experiments
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Huang, Linbin
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54 |
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p. 192-197
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artikel
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| 123 |
RaPId - A Parameter Estimation Toolbox for Modelica/FMI-Based Models Exploiting Global Optimization Methods
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Podlaski, Meaghan
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54 |
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p. 391-396
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artikel
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| 124 |
Recursive identification of errors-in-variables models with correlated output noise
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Barbieri, Matteo
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54 |
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p. 363-368
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artikel
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| 125 |
Recursive system identification for coefficient estimation of continuous-time fractional order systems
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Duhé, Jean-François
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54 |
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p. 114-119
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artikel
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| 126 |
Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems ⁎ ⁎ This work was supported by the National Science Foundation of China (No. 61903338), the Liaoning Provincial Natural Science Foundation of China (2019-KF-23-02), the Zhejiang Provincial Natural Science Foundation of China (No. LQ19F030015, No. LQ19F020013, No. LGF19F010008), the Swedish Research Council through the research environment NewLEAD-New Directions in Learning Dynamical Systems (contract 2016-06079) and the project 2019-04956.
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Fang, Mengyuan
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54 |
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p. 345-350
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artikel
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| 127 |
Robust Data-Driven Error Compensation for a Battery Model
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Gesner, Philipp
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54 |
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p. 256-261
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artikel
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| 128 |
Robust Reinforcement Learning for Stochastic Linear Quadratic Control with Multiplicative Noise ⁎ ⁎ This work has been supported in part by the U.S. National Science Foundation under Grants ECCS-1501044 and EPCN-1903781.
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Pang, Bo
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54 |
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p. 240-243
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artikel
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| 129 |
Robust System Identification for Anemia Management
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Affan, Affan
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54 |
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p. 328-333
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artikel
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| 130 |
Semi-parametric Regression based on Machine Learning Methods for UAS Stall Identification
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Guibert, Vincent
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54 |
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p. 180-185
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artikel
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| 131 |
Shaping multisine excitation for closed-loop identification of a flexible transmission
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Boukhebouz, Bassem
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54 |
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p. 643-648
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artikel
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| 132 |
Soft Sensor Transferability between Lines of a Sulfur Recovery Unit
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Curreri, F.
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p. 535-540
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artikel
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| 133 |
Stability of discrete-time feed-forward neural networks in NARX configuration
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Bonassi, Fabio
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p. 547-552
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artikel
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| 134 |
Stable Lasso for Model Structure Learning of Inferential Sensor Modeling
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Qin, S. Joe
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p. 228-233
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artikel
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| 135 |
State-space modal representations for decomposition of multivariate non-stationary signals
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Avendaño-Valencia, Luis David
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54 |
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p. 475-480
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artikel
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| 136 |
The Linear Functional Strategy for Maneuvers Identification Using Elastic Template Matching ⁎ ⁎ This work has been supported by the LCM K2 Center within the framework of the Austrian COMET-K2 program
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Tkachenko, Pavlo
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p. 427-432
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artikel
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| 137 |
The risk of making decisions from data through the lens of the scenario approach
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Garatti, Simone
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p. 607-612
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artikel
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| 138 |
Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming
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Nechita, Ştefan-Cristian
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54 |
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p. 379-384
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artikel
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| 139 |
Using the SDP identification method for electromechanical systems
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Janot, A.
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54 |
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p. 809-814
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artikel
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| 140 |
Variational State and Parameter Estimation ⁎ ⁎ This research was financially supported by the project Learning fexible models for nonlinear dynamics (contract number: 2017-03807), funded by the Swedish Research Council and by Kjell och Märta Beijer Foundation and by the project AI4Research at Uppsala University.
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Courts, Jarrad
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p. 732-737
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artikel
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| 141 |
Voltage State Estimation using a Power Network Model driven AutoEncoder Neural Network
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Mishra, Aditya
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p. 517-522
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