A shift in paradigm for system identification
System identification is a mature research area with well established paradigms, mostly
based on classical statistical methods. Recently, there has been considerable interest in so …
based on classical statistical methods. Recently, there has been considerable interest in so …
On kernel design for regularized LTI system identification
T Chen - Automatica, 2018 - Elsevier
There are two key issues for the kernel-based regularization method: one is how to design a
suitable kernel to embed in the kernel the prior knowledge of the LTI system to be identified …
suitable kernel to embed in the kernel the prior knowledge of the LTI system to be identified …
Bus arrival time prediction and reliability analysis: An experimental comparison of functional data analysis and Bayesian support vector regression
To maintain the stability and punctuality of bus systems, an accurate forecast of arrival time
is essential to devise control strategies to prevent bus bunching especially under congested …
is essential to devise control strategies to prevent bus bunching especially under congested …
On semiseparable kernels and efficient implementation for regularized system identification and function estimation
T Chen, MS Andersen - Automatica, 2021 - Elsevier
A long-standing problem for kernel-based regularization methods is their high computational
complexity O (N 3), where N is the number of data points. In this paper, we make a …
complexity O (N 3), where N is the number of data points. In this paper, we make a …
On the regularization and optimization in quantum detector tomography
Quantum detector tomography (QDT) is a fundamental technique for calibrating quantum
devices and performing quantum engineering tasks. In this paper, we utilize regularization to …
devices and performing quantum engineering tasks. In this paper, we utilize regularization to …
Asymptotic properties of generalized cross validation estimators for regularized system identification
In this paper, we study the asymptotic properties of the generalized cross validation (GCV)
hyperparameter estimator and establish its connection with the Stein's unbiased risk …
hyperparameter estimator and establish its connection with the Stein's unbiased risk …
Continuous-time DC kernel—a stable generalized first-order spline kernel
T Chen - IEEE Transactions on Automatic Control, 2018 - ieeexplore.ieee.org
The stable spline (SS) kernel and the diagonal correlated (DC) kernel are two kernels that
have been applied and studied extensively for kernel-based regularized LTI system …
have been applied and studied extensively for kernel-based regularized LTI system …
Informative Input Design for Dynamic Mode Decomposition
Efficiently estimating system dynamics from data is essential for minimizing data collection
costs and improving model performance. This work addresses the challenge of designing …
costs and improving model performance. This work addresses the challenge of designing …
Experiment design for impulse response identification with signal matrix models
This paper formulates an input design approach for truncated infinite impulse response
identification in the context of implicit model representations recently used as basis for data …
identification in the context of implicit model representations recently used as basis for data …
On embeddings and inverse embeddings of input design for regularized system identification
Input design is an important problem for system identification and has been well studied for
the classical system identification, ie, the maximum likelihood/prediction error method. For …
the classical system identification, ie, the maximum likelihood/prediction error method. For …