Ivan Markovsky

Eric Rogers, Ivan Markovsky, Marek Przedwojski, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

Data-Driven Tests for Controllability

Ivan Markovsky, Vikas Kumar Mishra, Ben Grossmann, 2021, IEEE Control Systems Letters.

Estimation in a linear multivariate measurement error model with a change point in the data

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2007, Comput. Stat. Data Anal..

Consistent least squares fitting of ellipsoids

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2004, Numerische Mathematik.

Comparison of Adaptive and Model-Free Methods for Dynamic Measurement

Ivan Markovsky, 2015, IEEE Signal Processing Letters.

Identification of electrically stimulated muscle models of stroke patients

Eric Rogers, Ivan Markovsky, Chris Freeman, 2010 .

Ultrasound Signal Reconstruction from Sparse Samples Using a Low-Rank and Joint-Sparse Model

Colas Schretter, Jan D'hooge, Ivan Markovsky, 2018, 2018 IEEE International Ultrasonics Symposium (IUS).

Structured low-rank approximation and its applications

Ivan Markovsky, I. Markovsky, 2008, Autom..

Total least squares and errors-in-variables modeling

Sabine Van Huffel, Torsten Söderström, Richard J. Vaccaro, 2007, Signal Process..

The element-wise weighted total least-squares problem

Sabine Van Huffel, Alexander Kukush, Maria Luisa Rastello, 2006, Comput. Stat. Data Anal..

Applications of Polynomial Common Factor Computation in Signal Processing

Nicola Guglielmi, Ivan Markovsky, Antonio Fazzi, 2018, LVA/ICA.

Realization and identification of autonomous linear periodically time-varying systems

Rik Pintelon, Ivan Markovsky, Konstantin Usevich, 2014, Autom..

A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints

Ting Kei Pong, Ivan Markovsky, Akiko Takeda, 2019, SIAM J. Matrix Anal. Appl..

When is a pole spurious

Bart De Moor, Ivan Markovsky, Katrien De Cock, 2007 .

Subspace identification with constraints on the impulse response

Ivan Markovsky, Guillaume Mercère, I. Markovsky, 2017, Int. J. Control.

Software package for mosaic-Hankel structured low-rank approximation

Ivan Markovsky, Konstantin Usevich, I. Markovsky, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Consistent fundamental matrix estimation in a quadratic measurement error model arising in motion analysis

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2002, Comput. Stat. Data Anal..

Overview of total least-squares methods

Sabine Van Huffel, Ivan Markovsky, I. Markovsky, 2007, Signal Process..

Structured Low-Rank Approximation with Missing Data

Ivan Markovsky, Konstantin Usevich, I. Markovsky, 2013, SIAM J. Matrix Anal. Appl..

Block-Toeplitz/Hankel Structured Total Least Squares

Sabine Van Huffel, Rik Pintelon, Ivan Markovsky, 2005, SIAM J. Matrix Anal. Appl..

Exact system identification with missing data

Ivan Markovsky, 2013, 52nd IEEE Conference on Decision and Control.

Factorization Approach to Structured Low-Rank Approximation with Applications

Ivan Markovsky, Konstantin Usevich, Mariya Ishteva, 2014, SIAM J. Matrix Anal. Appl..

Variable projection for affinely structured low-rank approximation in weighted 2-norms

Ivan Markovsky, Konstantin Usevich, 2014, J. Comput. Appl. Math..

System Identification in the Behavioral Setting - A Structured Low-Rank Approximation Approach

Ivan Markovsky, 2015, LVA/ICA.

Application of low-rank approximation for nonlinear system identification

Ivan Markovsky, 2017, 2017 25th Mediterranean Conference on Control and Automation (MED).

A Missing Data Approach to Data-Driven Filtering and Control

Ivan Markovsky, I. Markovsky, 2017, IEEE Transactions on Automatic Control.

Compressed Ultrasound Signal Reconstruction Using a Low-Rank and Joint-Sparse Representation Model

Colas Schretter, Ivan Markovsky, Miaomiao Zhang, 2019, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

A comparison between structured low-rank approximation and correlation approach for data-driven output tracking

Simone Formentin, Ivan Markovsky, 2018 .

Approximate system identification: Misfit versus latency

Ivan Markovsky, 2007 .

Optimization on a Grassmann manifold with application to system identification

Ivan Markovsky, Konstantin Usevich, I. Markovsky, 2014, Autom..

Low Rank Approximation - Algorithms, Implementation, Applications

Ivan Markovsky, I. Markovsky, 2018, Communications and Control Engineering.

Fast Measurements of Slow Processes

Ivan Markovsky, 2012 .

Bibliography on total least squares and related methods

Ivan Markovsky, I. Markovsky, 2010 .

Linear algebra with applications

Ivan Markovsky, 2009 .

System Identification of Muscle Dynamics for ILC-based Stroke Rehabilitation

Eric Rogers, Ivan Markovsky, Chris Freeman, 2009 .

Departement Elektrotechniek ESAT-SISTA / TR 2004-51 Application of Structured Total Least Squares for System Identification and Model Reduction 1

Sabine Van Huffel, Bart De Moor, Rik Pintelon, 2007 .

Model Construction and Control of Trapped Vortices

Eric Rogers, Ivan Markovsky, Owen Tutty, 2010 .

Recent progress on variable projection methods for structured low-rank approximation

Ivan Markovsky, I. Markovsky, 2014, Signal Process..

Online identification of electrically stimulated muscle models

Eric Rogers, Ivan Markovsky, Christopher Freeman, 2011, Proceedings of the 2011 American Control Conference.

Data-Driven Structured Noise Filtering via Common Dynamics Estimation

Akiko Takeda, Ivan Markovsky, Tianxiang Liu, 2020, IEEE Transactions on Signal Processing.

Regularized structured low-rank approximation with applications pdf

Ivan Markovsky, Konstantin Usevich, Mariya Ishteva, 2013, ArXiv.

Bias and covariance of the least squares estimate in a structured errors-in-variables problem

Dieter Verbeke, Rik Pintelon, Ivan Markovsky, 2020, Comput. Stat. Data Anal..

Identification of the Dynamics of Human Arms after Stroke

Eric Rogers, Ivan Markovsky, Chris Freeman, 2008 .

Innovation-based subspace identification in open- and closed-loop

Ivan Markovsky, Guillaume Mercère, José A. Ramos, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

On Weighted Structured Total Least Squares

Sabine Van Huffel, Ivan Markovsky, 2005, LSSC.

Linear dynamic filtering with noisy input and output

Bart De Moor, Ivan Markovsky, 2005, Autom..

Algorithms and Literate Programs for Weighted Low-Rank Approximation with Missing Data

Ivan Markovsky, I. Markovsky, 2011 .

Algorithms for deterministic balanced subspace identification

Bart De Moor, Jan C. Willems, Paolo Rapisarda, 2005, Autom..

An ODE-Based Method for Computing the Distance of Coprime Polynomials to Common Divisibility

Nicola Guglielmi, Ivan Markovsky, I. Markovsky, 2017, SIAM J. Numer. Anal..

Software for weighted structured low-rank approximation

Ivan Markovsky, Konstantin Usevich, I. Markovsky, 2014, J. Comput. Appl. Math..

Identification of electrically stimulated muscle after stroke

Eric Rogers, Christopher T. Freeman, Ivan Markovsky, 2009, 2009 European Control Conference (ECC).

Variable projection methods for approximate (greatest) common divisor computations pdf

Ivan Markovsky, Konstantin Usevich, 2017, Theor. Comput. Sci..

Least-Squares Contour Alignment

Sasan Mahmoodi, Ivan Markovsky, I. Markovsky, 2009, IEEE Signal Processing Letters.

On the Complex Least Squares Problem with Constrained Phase

Ivan Markovsky, 2011, SIAM J. Matrix Anal. Appl..

A Low-Rank and Joint-Sparse Model for Ultrasound Signal Reconstruction

Colas Schretter, Jan D'hooge, Ivan Markovsky, 2018 .

Identification of Linear Time-Invariant Systems From Multiple Experiments

Rik Pintelon, Ivan Markovsky, I. Markovsky, 2015, IEEE Transactions on Signal Processing.

Dealing with Prior Knowledge

Ivan Markovsky, I. Markovsky, 2018, Low-Rank Approximation.

The Set of Linear Time-Invariant Unfalsified Models With Bounded Complexity is Affine

Ivan Markovsky, Vikas Kumar Mishra, 2021, IEEE Transactions on Automatic Control.

Addition and intersection of linear time-invariant behaviors

Ivan Markovsky, Antonio Fazzi, 2021 .

Data-Driven Simulation for NARX Systems*

Ivan Markovsky, Antonio Fazzi, Philippe Dreesen, 2021, 2021 29th European Signal Processing Conference (EUSIPCO).

Common dynamic estimation via structured low-rank approximation with multiple rank constraints

Nicola Guglielmi, Ivan Markovsky, Antonio Fazzi, 2021, IFAC-PapersOnLine.

Behavioral systems theory in data-driven analysis, signal processing, and control

Florian Dörfler, Ivan Markovsky, I. Markovsky, 2021, Annu. Rev. Control..

Bridging Direct and Indirect Data-Driven Control Formulations via Regularizations and Relaxations

Ivan Markovsky, Florian Dorfler, Jeremy Coulson, 2021, IEEE Transactions on Automatic Control.

Generalized algorithms for the approximate matrix polynomial GCD of reducing data uncertainties with application to MIMO system and control

Nicola Guglielmi, Ivan Markovsky, Antonio Fazzi, 2021, J. Comput. Appl. Math..

How Effective Is the Nuclear Norm Heuristic in Solving Data Approximation Problems

Ivan Markovsky, 2012 .

On the conic section fitting problem

Sabine Van Huffel, Alexander Kukush, Sergiy Shklyar, 2007 .

About the convergence of the computational algorithm For The Ew-tls Estimator

Alexander Kukush, Ivan Markovsky, Sabine Van Hu el, 2002 .

Structured low-rank approximation as a rational function minimization

Ivan Markovsky, Konstantin Usevich, 2012 .

On errors-in-variables estimation with unknown noise variance ratio

Alexander Kukush, S. Van Huffel, Ivan Markovsky, 2006 .

On the computation of the structured total least squares estimator

Alexander Kukush, S. Van Huffel, Ivan Markovsky, 2004 .

Recursive Identification of Hammerstein Structure

Eric Rogers, Ivan Markovsky, Fengmin Le, 2011 .

An algorithm for approximate common divisor computation

Sabine Van Huffel, Ivan Markovsky, 2006 .

Linear Dynamic Filtering with Noisy Input and Output

Bart De Moor, Ivan Markovsky, 2003 .

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach (Mathematical Modeling and Computation) (Mathematical Modeling and Computation)

Sabine Van Huffel, Bart De Moor, Jan C. Willems, 2006 .

On the equivalence between total least squares and maximum likelihood PCA

S. Van Huffel, Peter D. Wentzell, Ivan Markovsky, 2005 .

Recursive Identification of Hammerstein Systems

Eric Rogers, Ivan Markovsky, Fengmin Le, 2011 .

Total least squares methods

Sabine Van Huffel, Ivan Markovsky, Diana Sima, 2010 .

Applications of structured low-rank approximation

Ivan Markovsky, 2009 .

On the linear quadratic data-driven control

Paolo Rapisarda, Ivan Markovsky, I. Markovsky, 2007, 2007 European Control Conference (ECC).

A MATLAB toolbox for weighted total least squares approximation

Ivan Markovsky, 2009 .

An adapted version of the element-wise weighted total least squares method for applications in chemometrics

S. Van Huffel, Ivan Markovsky, M. Schuermans, 2007 .

Progress and Open Questions in the Identification of Electrically Stimulated Human Muscle for Stroke Rehabilitation

Eric Rogers, Ivan Markovsky, Fengmin Le, 2012 .