C. R. Rojas

Latest

• 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