67 results on '"Lennart Ljung"'
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2. On the Influence of Ill-conditioned Regression Matrix on Hyper-parameter Estimators for Kernel-based Regularization Methods.
3. Asymptotic Properties of Hyperparameter Estimators by Using Cross-Validations for Regularized System Identification.
4. Subspace identification of continuous-time models using generalized orthonormal bases.
5. On the input design for kernel-based regularized LTI system identification: Power-constrained inputs.
6. On definition and inference of nonlinear Boolean dynamic networks.
7. Continuous-time DC kernel - A stable generalized first order spline kernel.
8. Developments towards formalizing a benchmark for continuous-time model identification.
9. Regularized system identification using orthonormal basis functions.
10. Spectral analysis of the DC kernel for regularized system identification.
11. Identifying biochemical reaction networks from heterogeneous datasets.
12. On the design of multiple kernels for nonparametric linear system identification.
13. Identification of wiener systems with process noise is a nonlinear errors-in-variables problem.
14. Stochastic Embedding revisited: A modern interpretation.
15. Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method.
16. Kernel-Based Model Order Selection for Linear System Identification.
17. What Can Regularization Offer for Estimation of Dynamical Systems?
18. Convexity issues in system identification.
19. Kernel-based model order selection for identification and prediction of linear dynamic systems.
20. Regularization strategies for nonparametric system identification.
21. Sparse control using sum-of-norms regularized model predictive control.
22. Rank-1 kernels for regularized system identification.
23. On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels.
24. Sparse multiple kernels for impulse response estimation with majorization minimization algorithms.
25. Kernel selection in linear system identification part II: A classical perspective.
26. A convex approach to subspace clustering.
27. On the accuracy of parameter estimation for continuous time nonlinear systems from sampled data.
28. Decentralization of particle filters using arbitrary state decomposition.
29. Trajectory generation using sum-of-norms regularization.
30. State smoothing by sum-of-norms regularization.
31. Modern Enterprise Systems as Enablers of Agile Development.
32. Revisiting the Two-Stage Algorithm for Hammerstein system identification.
33. On manifolds, climate reconstruction and bivalve shells.
34. The use of nonnegative garrote for order selection of ARX models.
35. Manifold-constrained regressors in system identification.
36. Direct Weight Optimization applied to discontinuous functions.
37. A robust particle filter for state estimation - with convergence results.
38. Connections between optimisation-based regressor selection and analysis of variance.
39. Consistent Nonparametric Estimation of NARX Systems Using Convex Optimization.
40. Well-posedness of Filtering Problems for Stochastic Linear DAE Models.
41. Integrated frequency-time domain tools for system identification.
42. State of the art in linear system identification: time and frequency domain methods.
43. Interactive analysis of time-varying systems using volume graphics.
44. Nonlinear dynamics isolated by delaunay triangulation criteria.
45. On consistency of closed-loop subspace identification with innovation estimation.
46. Local modelling with a priori known bounds using direct weight optimization.
47. Initialisation aspects for subspace and output-error identification methods.
48. A review of time-delay estimation techniques.
49. Identification for control: simple process models.
50. A non-asymptotic approach to local modelling.
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