Håkan Hjalmarsson
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CV
C. R. Rojas
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Parametric Identification Using Weighted Null-Space Fitting
A Least Squares Method for Identification of Feedback Cascade Systems
A graph theoretical approach to input design for identification of nonlinear dynamical models
A weighted least-squares method for parameter estimation in structured models
Advanced Autonomous Model-Based Operation of Industrial Process Systems (AutoProfit): Technological Developments and Future Perspectives
Applications Oriented Input Design for Closed-Loop System Identification: a Graph-Theory Approach
Identification of a Class of Nonlinear Dynamical Networks
On the Effect of Noise Correlation in Parameter Identification of SIMO Systems
Uncertainty in system identification: learning from the theory of risk
Variance Analysis of Linear SIMO Models with Spatially Correlated Noise
A simulated annealing approach to exact experiment design for dynamical systems
Application Set Approximation in Optimal Input Design for Model Predictive Control
Applications Oriented Input Design in Time-Domain Through Cyclic Methods
Iterative Data-Driven $H_ınfty$ Norm Estimation of Multivariable Systems with Application to Robust Active Vibration Isolation
Variance Results for Parallel Cascade Serial Systems
Least Squares End Performance Experiment Design in Multicarrier Systems: The Sparse Preamble Case
Piecewise Toeplitz Matrices-based Sensing for Rank Minimization
Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting
Analysis of averages over distributions of Markov processes
Cost function shaping of the output error criterion
A Weighted Least Squares Method for Estimation of Unstable Systems
Identification of Modules in Dynamic Networks: An Empirical Bayes Approach
An application-oriented approach to dual control with excitation for closed-loop identification
Piecewise sparse signal recovery via piecewise orthogonal matching pursuit
On Estimating Initial Conditions in Unstructured Models
On the Variance Analysis of identified Linear MIMO Models
Experimental evaluation of model predictive control with excitation (MPC-X) on an industrial depropanizer
Sparse estimation of polynomial and rational dynamical models
Input design as a tool to improve the convergence of PEM
A Note on the SPICE Method
Frequency smoothing gains in preamble-based channel estimation for multicarrier systems
Application-Oriented Least Squares Experiment Design in Multicarrier Communication Systems
A Geometric Approach to Variance Analysis of Cascaded Systems
A Sparse Estimation Technique for General Model Structures
Iteratively Learning the $H_ınfty$-Norm of Multivariable Systems Applied to Model-Error-Modeling of a Vibration Isolation System
Model predictive control with integrated experiment design for Output Error Systems
Optimal input design for non-linear dynamic systems: a graph theory approach
Analyzing Iterations in Identification with Application to Nonparametric $H_ınfty$-norm Estimation
Accuracy of Linear multiple-input multiple-output (MIMO) Models obtained by Maximum Likelihood Estimation
A Chernoff Relaxation on the Problem of Application-Oriented Finite Sample Experiment Design
A Tutorial on Applications-Oriented Optimal Experiment Design
Application-Oriented Finite Sample Experiment Design: A Semidefinite Relaxation Approach
Identification of Box-Jenkins models using structured ARX models and nuclear norm relaxation
Mean-squared error experiment design for linear regression models
On the convergence of the prediction error method to its global minimum
Order and Structural Dependence Selection of LPV-ARX Models Revisited
Preface to System identification: A Wiener-Hammerstein benchmark
Robust Experiment Design for System Identification via Semi-Infinite Programming Techniques
Sparse Estimation Techniques for Basis Function Selection in Wideband System Identification
Sparse Estimation of Rational Dynamical Models
On the accuracy in errors-in-variables identification compared to prediction-error identification
The Cost of Complexity in System Identification: The Output Error Case
Predictor-based multivariable closed-loop system identification of the EXTRAP T2R reversed field pinch external plasma response
An adaptive method for consistent estimation of real-valued non-minimum zeros in stable LTI systems
Conditions when minimum variance control is the optimal experiment for identifying a minimum variance controller
Analyzing Iterations in Identification with Application to Nonparametric $mathcalH_infty$-norm Estimation
Cascade and multibatch subspace system identification for multivariate vacuum-plasma response characterisation
Chance Constrained Input Design
MPC oriented experiment design
Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging
Sparse estimation based on a validation criterion
D3.1. Methodologies for identification and model management of large-scale systems
Closed-Loop MIMO ARX Estimation of Concurrent External Plasma Response Eigenmodes in Magnetic Confinement Fusion
Identification of Nonlinear Systems Using Misspecified Predictors
On Optimal Input Design for Nonlinear FIR-Type Systems
The Cost of Complexity in System Identification: Frequency Function Estimation of Finite Impulse Response Systems
Finite Model Order Optimal Input Design for Minimum Variance Control
Consistent estimation of real NMP zeros in stable LTI systems of arbitrary complexity
Input Design for Asymptotic Robust $H_2$-Filtering
MIMO Experiment Design based on Asymptotic Model Order Theory
Vector dither experiment design and direct parametric identification of reversed-field pinch normal modes
The cost of complexity in identification of FIR systems
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