- Linear Prediction Error Methods for Stochastic Nonlinear Models
- Bayesian nonparametric estimation of Wiener systems
- Identification of linear models from quantized data: a midpoint-projection approach
- Learning robust LQ-controllers using application oriented exploration
- Modeling and identification of uncertain-input systems
- Nonlinear System Identification Using Optimal Estimating Functions
- Parametric Identification Using Weighted Null-Space Fitting
- Performance analysis of Iterative Feedback Tuning
- The Weighted Null-Space Fitting Method for Identification of Multivariate Model Structures
- A Least Squares Method for Identification of Feedback Cascade Systems
- A Sequential Least Squares Algorithm for ARMAX Dynamic Network Identification
- A benchmark for data-based office modeling: challenges related to CO$_2$ dynamics
- A graph theoretical approach to input design for identification of nonlinear dynamical models
- A kernel-based approach to Hammerstein system identification
- A new kernel-based approach to system identification with quantized output data
- 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
- Analysis of two methods for nonparametric Frequency Response Function identification
- Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem
- Application-Oriented Input Design in System Identification Optimal input design for control
- Applications Oriented Input Design for Closed-Loop System Identification: a Graph-Theory Approach
- Approximate Maximum-Likelihood Identification of Linear Systems from Quantized Measurements
- Bayesian kernel-based system identification with quantized output data
- Blind identification strategies for room occupancy estimation
- Blind system identification using kernel-based methods
- Blind system identification using kernel-based methods
- EM-based Hyperparameter Optimization for Regularized Volterra Kernel Estimation
- Identification of a Class of Nonlinear Dynamical Networks
- Nonlinear FIR Identification with Model Order Reduction Steiglitz-McBride
- On the Effect of Noise Correlation in Parameter Identification of SIMO Systems
- On the variance of identified SIMO systems with spatially correlated output noise
- Uncertainty in system identification: learning from the theory of risk
- Variance Analysis of Linear SIMO Models with Spatially Correlated Noise
- Weighted Null-Space Fitting for Identification of Cascade Networks
- 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
- Experiment design for parameter estimation in nonlinear systems based on multilevel excitation
- Input Signal Generation for Constrained Multiple-Input Multple-Output Systems
- Iterative Data-Driven $H_ınfty$ Norm Estimation of Multivariable Systems with Application to Robust Active Vibration Isolation
- Optimal Experiment Design in Closed Loop with Unknown Nonlinear or Implicit Controllers using Stealth Identification
- Outlier robust system identification: a Bayesian kernel-based approach
- Variance Results for Parallel Cascade Serial Systems
- Analysis of TCP/IP over WCDMA Wireless Systems under Power Control, MAI and Link Level Error Recovery
- Applications of mixed $mathcal H_ınfty$ and $mathcal H_2$ input design in identification
- Validation of stability for an induction machine drive using power iterations
- From experiments to closed loop control
- Randomized Iterative Feedback Tuning
- Tuning for robustness and performance using Iterative Feedback Tuning
- Convergence and Asymptotic Efficiency of the Box-Jenkins Stegilitz McBride Method: The Open Loop Case
- Distributed Signal Recovery Via Piecewise Orthogonal Matching Pursuit and Finite-Time Consensus
- Least Costly Closed-loop Performance Diagnosis and Plant Re-identication
- Least Squares End Performance Experiment Design in Multicarrier Systems: The Sparse Preamble Case
- Piecewise Toeplitz Matrices-based Sensing for Rank Minimization
- Training Sequence Design for MIMO Channels: An Application-Oriented Approach
- Identification for Control of Multivariable Systems: Controller Validation and Experiment Design via LMIs
- A General Framework for Iterative Learning Control
- Accurate quantification of variance error
- Closed loop identification of unstable poles and non-minimum phase zeros
- Exact Quantification of variance error
- From open loop learning to closed loop control
- Identification of non-minimum phase zeros in open and closed loop
- Identification of performance limitations using ARX models
- Identification of performance limitations using general SISO structures
- Input design for identification of zeros
- Model Based Design Variables for Iterative Learning Control of Nonlinear Systems
- On direct estimation of physical parameters in nonlinear models
- On explicit characterisation of reproducing kernels with applications in estimation theory
- On frequency Domain Accuracy of Closed Loop Estimates
- On methods for gradient estimation in IFT for MIMO systems
- Optimal experiment design in closed loop
- The Analysis of Variance Error Part I: Fundamental Principles
- The Analysis of Variance Error Part II: Accurate Quantification
- Unbiased bandwidth estimation in communication protocols
- Using a sufficient condition to analyze the interplay between identification and control
- Using local and global information in identification for control
- Efficient Tuning of Linear Multivariable Controllers Using Iterative Feedback Tuning
- Model-free Tuning of a Robust Regulator for a Flexible Transmission System
- Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting
- Stability and Performance Analysis of Control Based on Incomplete Models
- Toward Tractable Global Solutions to Maximum-Likelihood Estimation Problems via Sparse Sum-of-Squares Relaxations
- Analysis of averages over distributions of Markov processes
- Approximate Maximum-Likelihood Identification of Linear Systems Weighted Null-Space Fitting for Cascade Networks with Arbitrary Location of Sensors and Excitation Signals
- Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors
- Outlier-robust estimation of uncertain-input systems with applications to nonparametric FIR and Hammerstein models
- Semi-parametric kernel-based identification of Wiener systems
- Outlier-robust estimation of uncertain-input systems with applications to nonparametric FIR and Hammerstein models
- An empirical Bayes approach to identification of modules in dynamic networks
- Open-loop asymptotically efficient model reduction with the Steiglitz-McBride method
- Optimal identification experiment design for the interconnection of locally controlled systems
- Hierarchical Robust Analysis for Identified Systems in Network
- Recursive Identification Based on Weighted Null-Space Fitting
- A nonparametric kernel-based approach to Hammerstein system identification
- On anti-aliasing filtering and oversampling scheme in system identification
- Approximate inference of nonparametric Hammerstein models
- Incorporating noise modeling in dynamic networks using non-parametric models
- On maximum likelihood identification of errors-in-variables models
- Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models
- Variational Bayes identification of acyclic dynamic networks
- Adaptive Experiment Design for LTI systems
- Covariance Analysis in SISO Linear Systems Identification
- Cost function shaping of the output error criterion
- A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems
- A Weighted Least Squares Method for Estimation of Unstable Systems
- Identification of Modules in Dynamic Networks: An Empirical Bayes Approach
- Kernel-Based System Identification from Noisy and Incomplete Input-Output Data
- The Transient Impulse Response Modeling Method for Non-parametric System Identification
- An application-oriented approach to dual control with excitation for closed-loop identification
- Robust EM kernel-based methods for linear system identification
- Generation of signals with specified seond order properties for constrained systems
- Piecewise sparse signal recovery via piecewise orthogonal matching pursuit
- The Box-Jenkins Steiglitz McBride Method
- A new kernel-based approach for overparameterized Hammerstein system identification
- Multi-room occupancy estimation through adaptive gray-box models
- On Estimating Initial Conditions in Unstructured Models
- On the Variance Analysis of identified Linear MIMO Models
- On the estimation of initial conditions in kernel-based system identification
- Outlier robust kernel-based system identification using l1-Laplace techniques
- A Multi-Time-Scale Generalization of Recursive Identification Algorithm for ARMAX Systems
- Almost sure stability and stabilization of discrete-time stochastic systems
- Experimental evaluation of model predictive control with excitation (MPC-X) on an industrial depropanizer
- The conservation of information, towards an axiomatized modular modeling approach to congestion control
- Re-weighting, Regularization Selection, and Transient in Nuclear Norm based Identification
- Sparse estimation of polynomial and rational dynamical models
- Variance Analysis of Identified Linear MISO Models Having Spatially Correlated Inputs, With Application to Parallel Hammerstein 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
- Generation of excitation signals with prescribed autocorrelation for input and output constrained systems
- 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
- Providing improvements in relation to a model of a process
- Robust and Adaptive Excitation Signal Generation for Input and Output Constrained Systems
- Analyzing Iterations in Identification with Application to Nonparametric $H_ınfty$-norm Estimation
- Finite model order accuracy in Hammerstein model estimation
- Recursive estimators with Markovian jumps
- Accuracy of Linear multiple-input multiple-output (MIMO) Models obtained by Maximum Likelihood Estimation
- On the Performance of Optimal Input Signals for Frequency Response Estimation
- A Chernoff Relaxation on the Problem of Application-Oriented Finite Sample Experiment Design
- A Mathematica Toolbox for Signals, Systems and Identification
- A Tutorial on Applications-Oriented Optimal Experiment Design
- A Unified Experiment Design Framework for Detection and Identification in Closed-Loop Performance Diagnosis
- Adaptive experiment design for ARMAX systems
- Application-Oriented Finite Sample Experiment Design: A Semidefinite Relaxation Approach
- Correlation of Distortion Noise Between the Branches of MIMO Transmit Antennas
- Identification for Automotive Systems
- Identification of Box-Jenkins models using structured ARX models and nuclear norm relaxation
- Mean-squared error experiment design for linear regression models
- Non-parametric Frequency Function Estimation using Transient Impulse Response Modelling
- 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
- System Identification for Automotive Systems: Opportunities and Challenges
- The Transient Impulse Response Modeling Method and the Local Polynomial Method for nonparametric system identification
- A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence
- 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
- A Least Squares Approach to Direct Frequency Response Estimation
- An axiomatic fluid-flow model for congestion control analysis
- 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
- Four encounters with System identification
- Input design using cylindrical algebraic decomposition
- MPC oriented experiment design
- On Optimal Input Design for Model Predictive Control
- On estimation of the gain of a dynamical system
- Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging
- Sparse estimation based on a validation criterion
- Queue Dynamics with Window Flow Control
- System identification of complex and structured systems. Parts I and II
- Identification for robust $H_2$ deconvolution filtering
- Closed-Loop MIMO ARX Estimation of Concurrent External Plasma Response Eigenmodes in Magnetic Confinement Fusion
- Identification of Nonlinear Systems Using Misspecified Predictors
- MPC oriented experiment design
- Non-parametric methods for $L_2$-Gain Estimation using Iterative Experiments
- Nonlinear State-Dependent Delay Modeling and Stability Analysis of Internet Congestion Control
- On Optimal Input Design for Nonlinear FIR-Type Systems
- The Cost of Complexity in System Identification: Frequency Function Estimation of Finite Impulse Response Systems
- A System, Signals and Identification Toolbox in Mathematica with Symbolic Capabilities
- Consistent estimation of real NMP zeros in stable LTI systems of arbitrary complexity
- Data-Driven Methods for $L_2$-Gain Estimation
- Optimal input design for robust $H_2$ deconvolution filtering
- Tuning of dissolved oxygen and pH PID control parameters in large scale bioreactor by lag control
- An Improved Link Model for Window Flow Control and Its Application to FAST TCP
- Improving TCP Performance During the LTE Handover
- Input Design for Asymptotic Robust $H_2$-Filtering
- MIMO Experiment Design based on Asymptotic Model Order Theory
- On Performance Limitations of Congestion Control
- System identification of complex and structured systems
- System identification of complex and structured systems
- Variance Results for Identification of Cascade Systems
- Vector dither experiment design and direct parametric identification of reversed-field pinch normal modes
- Variance Analysis of Identification of Cascade Systems
- ACK-Clocking Dynamics: Modeling the Interaction between ACK-Clock and Network
- On identification of cascade systems
- Window flow control: Macroscopic properties from microscopic factors
- A Geometric Approach to Variance Analysis in System Identification: Linear Time-Invariant Systems
- A Geometric Approach to Variance Analysis in System Identification: Theory and Nonlinear Systems
- Prediction of Engine Noise using Parameterized Combustion Pressure Curves
- ACK-clock Dynamics in Network Congestion Control -- An Inner Feedback Loop with Implications on Inelastic Flow Impact
- A control perspective on optimal input design in system identification
- Conclusions of the ARTIST2 Roadmap on Control of Computing Systems
- Conclusions from the European Roadmap on Control of Computing Systems
- Input Design via LMIs Admitting Frequency-wise Model Specifications in Confidence Regions
- Numerical Conditioning
- Variance Error, Reproducing Kernels and Orhonormal Bases
- Application of mixed $mathcal H_ınfty$ and $mathcal H_2$ input design to identification for control
- Variance Error Quantifications that are Exact for Finite Model Order
- Relay auto-tuning of PID controllers using iterative feedback tuning
- Iterative Feedback Tuning --An overview
- On Router Control for Congestion Avoidance
- Randomization methods in optimization and adaptive control
- Signalteori
- Model Structure and Numerical Properties of Normal Equations
- Identification of Performance Limitations in Control
- Robust loopshaping using Iterative Feedback Tuning
- Spectral Matching for parameter estimation in nonlinear input-output models
- Improved and quantified accuracy for linear spectral estimates
- Optimal Input Design Using Linear Matrix Inequalities
- The fundamental role of general orthonormal bases in system identification
- Asymptotic Variance Expressions for Output Error Model Structures
- Estimation Variance is not Model Structure Independent
- Iterative Feedback Tuning of controllers in cold rolling mills
- Maximum Likelihood Estimation of Models with Unstable Dynamics and Non-minimum Phase Noise Zeros
- Model Structure and Numerical Properties of Normal Equations
- Signal Spectra and Conditioning when using Orthonormal Parametrisation
- Tuning of controllers and generalized hold functions in sampled-data systems using Iterative Feedback Tuning
- Generalised Fourier and Toeplitz results for rational orthonormal bases
- Iterative Feedback Tuning: theory and applications
- Optimally Robust System Identification of Systems Subject to Amplitude Bounded Stochastic Disturbances
- Control of nonlinear systems using Iterative Feedback Tuning
- Fast non-iterative estimation of hidden Markov models
- Generalized Fourier and Toeplitz results for rational orthonormal bases.
- Identification in closed loop: Asymptotic high order variance for restricted complexity models
- Iterative Feedback Tuning
- Iterative Feedback Tuning of linear time-invariant MIMO systems
- Frequency domain expressions of the accuracy of a model free control design scheme
- Iterative Feedback Tuning: theory and applications in chemical process control
- Significance Regression: A Statistical Approach to Partial Least Squares
- For model based control design criteria, closed loop identification gives better performance
- On the choice of norms in system identification
- Modelling of Random Processes using Orthonormal Bases
- On Neural Network Model Structures in System Identification
- Optimal robust system identification: Bounded stochastic disturbances
- 21 ML estimators for model selection
- Composite Modeling of Transfer Functions
- Composite Modeling of Transfer Functions
- Model-Free Tuning of Controllers: Experience with Time-Varying Linear Systems
- Model-Free Tuning of a Robust Regulator for a Flexible Transmission System
- Nonlinear Black-Box Models in System Identification: Mathematical Foundations
- Nonlinear Black-Box Models in System Identification: a Unified Overview
- Optimality and Sub-optimality of Iterative Identification and Control Design Schemes
- System Identification through the eyes of Model Validation
- A Convergent Iterative Restricted Complexity Control Design Scheme
- A Unifying View of Disturbances in Identification
- Identification for control: Closing the loop gives more accurate controllers
- Neural Networks in System Identification
- Non-Vanishing Model Errors
- On the choice of norms i system identification
- The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise
- The least-squares identification of FIR systems subject to worst-case noise
- A Discussion of "Unknown-but-Bounded" Disturbances in System Identification
- A Model Variance Estimator
- Aspects on Incomplete Modeling in System Identification
- Asymptotic Correct Correlation Tests in Model Validation
- Detecting Asymptotically Non-Vanishing Model Uncertainty
- Nineteen ML Estimators for Model Structure Selection
- Estimating Model Variance in the Case of Undermodeling
- An Invariance Principle for "reverse" Mixingales
- Asymptotic Relations Between Non-Weighted and Exponentially Weighted Series: A Functional Limit Approach
- Some Reflections on Control Design Based on Experimental Data
- Estimation of the variability of time-varying systems
- Model Quality: The Role of Prior Knowledge and Data Information
- How to estimate model uncertainty in the case of under-modelling
- On Estimation of Model Quality in System Identification

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