An approach to integral input-to-state stabilization via satisficing strategy. - Tianshi Chen 001; Zhiyuan Liu 005; Run Pei; Hong Chen 003 (ICARCV, 2004)

Inverse optimal constrained input-to-state stabilization of nonlinear systems. - Tianshi Chen 001; Zhiyuan Liu 005; Hong Chen 003; Run Pei (ACC, 2005)

Global robust stabilization of a class of uncertain feedforward systems. - Tianshi Chen 001; Jie Huang 001 (CDC, 2007)

Global robust stabilization of nonlinear strict feedforward systems with input unmodeled dynamics. - Tianshi Chen 001; Jie Huang 001 (ACC, 2008)

Disturbance Attenuation of Feedforward Systems With Dynamic Uncertainty. - Tianshi Chen 001; Jie Huang 001 (IEEE Trans. Autom. Control., 2008)

Global Robust Output Regulation by State Feedback for Strict Feedforward Systems. - Tianshi Chen 001; Jie Huang 001 (IEEE Trans. Autom. Control., 2009)

Decentralization of particle filters using arbitrary state decomposition. - Tianshi Chen 001; Thomas B. Schön; Henrik Ohlsson; Lennart Ljung (CDC, 2010)

Comments on "State estimation for linear systems with state equality constraints" [Automatica 43 (2007) 1363-1368]. - Tianshi Chen 001 (Autom., 2010)

A small gain approach to global stabilization of nonlinear feedforward systems with input unmodeled dynamics. - Tianshi Chen 001; Jie Huang 001 (Autom., 2010)

Kernel selection in linear system identification part II: A classical perspective. - Tianshi Chen 001; Henrik Ohlsson; Graham C. Goodwin; Lennart Ljung (CDC/ECC, 2011)

Decentralized Particle Filter With Arbitrary State Decomposition. - Tianshi Chen 001; Thomas B. Schön; Henrik Ohlsson; Lennart Ljung (IEEE Trans. Signal Process., 2011)

On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels. - Ruggero Carli; Tianshi Chen 001; Alessandro Chiuso; Lennart Ljung; Gianluigi Pillonetto (CDC, 2012)

Sparse multiple kernels for impulse response estimation with majorization minimization algorithms. - Tianshi Chen 001; Lennart Ljung; Martin S. Andersen 001; Alessandro Chiuso; Francesca Paola Carli; Gianluigi Pillonetto (CDC, 2012)

On the estimation of transfer functions, regularizations and Gaussian processes - Revisited. - Tianshi Chen 001; Henrik Ohlsson; Lennart Ljung (Autom., 2012)

What Can Regularization Offer for Estimation of Dynamical Systems? - Lennart Ljung; Tianshi Chen 001 (ALCOSP, 2013)

Kernel-Based Model Order Selection for Linear System Identification. - Gianluigi Pillonetto; Tianshi Chen 001; Lennart Ljung (ALCOSP, 2013)

Rank-1 kernels for regularized system identification. - Tianshi Chen 001; Alessandro Chiuso; Gianluigi Pillonetto; Lennart Ljung (CDC, 2013)

Regularization strategies for nonparametric system identification. - Alessandro Chiuso; Tianshi Chen 001; Lennart Ljung; Gianluigi Pillonetto (CDC, 2013)

Kernel-based model order selection for identification and prediction of linear dynamic systems. - Gianluigi Pillonetto; Tianshi Chen 001; Lennart Ljung (CDC, 2013)

Convexity issues in system identification. - Lennart Ljung; Tianshi Chen 001 (ICCA, 2013)

Implementation of algorithms for tuning parameters in regularized least squares problems in system identification. - Tianshi Chen 001; Lennart Ljung (Autom., 2013)

Scalable Anomaly Detection in Large Homogenous Populations. - Henrik Ohlsson; Tianshi Chen 001; Sina Khoshfetrat Pakazad; Lennart Ljung; S. Shankar Sastry (CoRR, 2013)

Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method. - Tianshi Chen 001; Martin S. Andersen 001; Alessandro Chiuso; Gianluigi Pillonetto; Lennart Ljung (CDC, 2014)

On the design of multiple kernels for nonparametric linear system identification. - Alessandro Chiuso; Tianshi Chen 001; Lennart Ljung; Gianluigi Pillonetto (CDC, 2014)

Scalable anomaly detection in large homogeneous populations. - Henrik Ohlsson; Tianshi Chen 001; Sina Khoshfetrat Pakazad; Lennart Ljung; S. Shankar Sastry (Autom., 2014)

Kernel methods in system identification, machine learning and function estimation: A survey. - Gianluigi Pillonetto; Francesco Dinuzzo; Tianshi Chen 001; Giuseppe De Nicolao; Lennart Ljung (Autom., 2014)

Maximum Entropy Property of Discrete-time First Order Stable Spline Kernel. - Tohid Ardeshiri; Tianshi Chen 001 (CoRR, 2014)

System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques. - Tianshi Chen 001; Martin S. Andersen 001; Lennart Ljung; Alessandro Chiuso; Gianluigi Pillonetto (IEEE Trans. Autom. Control., 2014)

Spectral analysis of the DC kernel for regularized system identification. - Tianshi Chen 001; Gianluigi Pillonetto; Alessandro Chiuso; Lennart Ljung (CDC, 2015)

Regularized system identification using orthonormal basis functions. - Tianshi Chen 001; Lennart Ljung (ECC, 2015)

Maximum entropy property of discrete-time stable spline kernel. - Tohid Ardeshiri; Tianshi Chen 001 (ICASSP, 2015)

Continuous-time DC kernel - A stable generalized first order spline kernel. - Tianshi Chen 001; Gianluigi Pillonetto; Alessandro Chiuso; Lennart Ljung (CDC, 2016)

Maximum entropy properties of discrete-time first-order stable spline kernel. - Tianshi Chen 001; Tohid Ardeshiri; Francesca P. Carli; Alessandro Chiuso; Lennart Ljung; Gianluigi Pillonetto (Autom., 2016)

Transfer function and transient estimation by Gaussian process regression in the frequency domain. - John Lataire; Tianshi Chen 001 (Autom., 2016)

Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint. - Gianluigi Pillonetto; Tianshi Chen 001; Alessandro Chiuso; Giuseppe De Nicolao; Lennart Ljung (Autom., 2016)

On kernel design for regularized LTI system identification. - Tianshi Chen 001; Lennart Ljung (CoRR, 2016)

Background of shape contexts for point matching. - Deheng Qian; Tianshi Chen 001; Hong Qiao (Pattern Recognit. Lett., 2016)

On the input design for kernel-based regularized LTI system identification: Power-constrained inputs. - Bi-Qiang Mu; Tianshi Chen 001; Lennart Ljung (CDC, 2017)

Maximum Entropy Kernels for System Identification. - Francesca Paola Carli; Tianshi Chen 001; Lennart Ljung (IEEE Trans. Autom. Control., 2017)

Asymptotic Properties of Hyperparameter Estimators by Using Cross-Validations for Regularized System Identification. - Bi-Qiang Mu; Tianshi Chen 001; Lennart Ljung (CDC, 2018)

Sparse Structure Enabled Grid Spectral Mixture Kernel for Temporal Gaussian Process Regression. - Feng Yin; Xinwei He; Lishuo Pan; Tianshi Chen 001; Zhi-Quan Tom Luo; Sergios Theodoridis (FUSION, 2018)

On kernel design for regularized LTI system identification. - Tianshi Chen 001 (Autom., 2018)

On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses. - Tianshi Chen 001; Gianluigi Pillonetto (Autom., 2018)

On input design for regularized LTI system identification: Power-constrained input. - Bi-Qiang Mu; Tianshi Chen 001 (Autom., 2018)

On asymptotic properties of hyperparameter estimators for kernel-based regularization methods. - Bi-Qiang Mu; Tianshi Chen 001; Lennart Ljung (Autom., 2018)

Continuous-Time DC Kernel - A Stable Generalized First-Order Spline Kernel. - Tianshi Chen 001 (IEEE Trans. Autom. Control., 2018)

Recursive Implementation of Gaussian Process Regression for Spatial-Temporal Data Modeling. - Ye Kuang; Tianshi Chen 001; Feng Yin; Renxin Zhong (WCSP, 2019)

Parameter estimation of discrete-time sinusoidal signals: A nonlinear control approach. - Teng Jiang; Dabo Xu; Tianshi Chen 001; Andong Sheng (Autom., 2019)

Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series. - Feng Yin; Lishuo Pan; Xinwei He; Tianshi Chen 001; Sergios Theodoridis; Zhi-Quan Tom Luo (CoRR, 2019)

Distributed Gaussian Processes Hyperparameter Optimization for Big Data Using Proximal ADMM. - Ang Xie; Feng Yin; Yue Xu; Bo Ai 001; Tianshi Chen 001; Shuguang Cui (IEEE Signal Process. Lett., 2019)

Cramér-Rao Bounds for Filtering Based on Gaussian Process State-Space Models. - Yuxin Zhao 003; Carsten Fritsche; Gustaf Hendeby; Feng Yin; Tianshi Chen 001; Fredrik Gunnarsson (IEEE Trans. Signal Process., 2019)

On the Influence of Ill-conditioned Regression Matrix on Hyper-parameter Estimators for Kernel-based Regularization Methods. - Yue Ju; Tianshi Chen 001; Bi-Qiang Mu; Lennart Ljung (CDC, 2020)

Regularized LTI system identification in the presence of outliers: A variational EM approach. - Martin Lindfors; Tianshi Chen 001 (Autom., 2020)

On Effects of Condition Number of Regression Matrix upon Hyper-parameter Estimators for Kernel-based Regularization Methods. - Yue Ju; Tianshi Chen 001; Bi-Qiang Mu; Lennart Ljung (CoRR, 2020)

Accelerated Sparse Bayesian Learning via Screening Test and Its Applications. - Yiping Jiang; Tianshi Chen 001 (CoRR, 2020)

A shift in paradigm for system identification. - Lennart Ljung; Tianshi Chen 001; Bi-Qiang Mu (Int. J. Control, 2020)

Smoothing Splines and Rank Structured Matrices: Revisiting the Spline Kernel. - Martin S. Andersen 001; Tianshi Chen 001 (SIAM J. Matrix Anal. Appl., 2020)

Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series. - Feng Yin; Lishuo Pan; Tianshi Chen 001; Sergios Theodoridis; Zhi-Quan Tom Luo; Abdelhak M. Zoubir (IEEE Trans. Signal Process., 2020)

On Asymptotic Distribution of Generalized Cross Validation Hyper-parameter Estimator for Regularized System Identification*. - Yue Ju; Tianshi Chen 001; Bi-Qiang Mu; Lennart Ljung (CDC, 2021)

Bus arrival time prediction and reliability analysis: An experimental comparison of functional data analysis and Bayesian support vector regression. - Yunping Huang; C. Chen; Z. C. Su; Tianshi Chen 001; Agachai Sumalee; Tianlu Pan; Renxin Zhong (Appl. Soft Comput., 2021)

On semiseparable kernels and efficient implementation for regularized system identification and function estimation. - Tianshi Chen 001; Martin S. Andersen 001 (Autom., 2021)

Kalman filtering under unknown inputs and norm constraints. - He Kong; Mao Shan; Salah Sukkarieh; Tianshi Chen 001; Wei Xing Zheng 001 (Autom., 2021)

Identification of Switched Linear Systems: Persistence of Excitation and Numerical Algorithms. - Bi-Qiang Mu; Tianshi Chen 001; Changming Cheng; Er-Wei Bai (CoRR, 2021)

Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model. - Yue Ju; Tianshi Chen 001; Bi-Qiang Mu; Lennart Ljung (CoRR, 2021)

Persistence of excitation for identifying switched linear systems. - Bi-Qiang Mu; Tianshi Chen 001; Changming Cheng; Er-Wei Bai (Autom., 2022)

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyper-parameter Estimator. - Yue Ju; Bi-Qiang Mu; Lennart Ljung; Tianshi Chen 001 (CoRR, 2022)

The noise covariances of linear Gaussian systems with unknown inputs are not uniquely identifiable using autocovariance least-squares. - He Kong; Salah Sukkarieh; Travis J. Arnold; Tianshi Chen 001; Wei Xing Zheng 001 (Syst. Control. Lett., 2022)

Towards Scalable Kernel-Based Regularized System Identification. - Lujing Chen; Tianshi Chen 001; Utkarsh Detha; Martin S. Andersen 001 (CDC, 2023)

An Efficient Implementation for Kernel-Based Regularized System Identification with Periodic Input Signals. - Zhuohua Shen; Yu Xu; Martin S. Andersen 001; Tianshi Chen 001 (CDC, 2023)

A Family of Hyper-parameter Estimators for Regularized Linear System Identification. - Meng Zhang; Tianshi Chen 001; Biqiang Mu (CDC, 2023)

An Efficient Implementation for Bayesian Manifold Regularization Method. - Junpeng Zhang; Yue Ju; Bo Wahlberg; Biqiang Mu; Tianshi Chen 001 (CDC, 2023)

On embeddings and inverse embeddings of input design for regularized system identification. - Biqiang Mu; Tianshi Chen 001; He Kong; Bo Jiang 010; Lei Wang 126; Junfeng Wu 001 (Autom., 2023)

An efficient implementation for spatial-temporal Gaussian process regression and its applications. - Junpeng Zhang; Yue Ju; Biqiang Mu; Renxin Zhong; Tianshi Chen 001 (Autom., 2023)

Identifiability Analysis of Noise Covariances for LTI Stochastic Systems With Unknown Inputs. - He Kong; Salah Sukkarieh; Travis J. Arnold; Tianshi Chen 001; Biqiang Mu; Wei Xing Zheng 001 (IEEE Trans. Autom. Control., 2023)

Kernel-based regularized iterative learning control of repetitive linear time-varying systems. - Xian Yu; Xiaozhu Fang; Biqiang Mu; Tianshi Chen 001 (Autom., 2023)

Input Design for Regularized System Identification: Stationary Conditions and Sphere Preserving Algorithm. - Biqiang Mu; He Kong; Tianshi Chen 001; Bo Jiang 010; Lei Wang 059; Junfeng Wu 001 (IEEE Trans. Autom. Control., 2023)

Data-Driven Distributed Adaptive Consensus Tracking of Nonlinear Multiagent Systems: A Controller-Based Dynamic Linearization Method. - Xian Yu; Zhongsheng Hou; Tianshi Chen 001 (IEEE Trans. Syst. Man Cybern. Syst., 2023)

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyperparameter Estimator. - Yue Ju; Biqiang Mu; Lennart Ljung; Tianshi Chen 001 (IEEE Trans. Autom. Control., 2023)

Kernel-Based Regularized Continuous-Time System Identification from Sampled Data. - Xiaozhu Fang; Biqiang Mu; Tianshi Chen 001 (CDC, 2024)

Asymptotic properties of generalized maximum likelihood hyper-parameter estimator for regularized system identification. - Meng Zhang; Tianshi Chen 001; Biqiang Mu (CDC, 2024)

A Class of Convex Optimization-Based Recursive Algorithms for Identification of Stochastic Systems. - Mingxia Ding; Wenxiao Zhao; Tianshi Chen 001 (CoRR, 2024)

A Local Gaussian Process Regression Approach to Frequency Response Function Estimation. - Xiaozhu Fang; Yu Xu; Tianshi Chen 001 (CoRR, 2024)

On kernel design for regularized non-causal system identification. - Xiaozhu Fang; Tianshi Chen 001 (Autom., 2024)

When cannot regularization improve the least squares estimate in the kernel-based regularized system identification. - Biqiang Mu; Lennart Ljung; Tianshi Chen 001 (Autom., 2024)

On Asymptotic Optimality of Cross-Validation Estimators for Kernel-Based Regularized System Identification. - Biqiang Mu; Tianshi Chen 001 (IEEE Trans. Autom. Control., 2024)

Distributed Iterative Learning Control of Nonlinear Multiagent Systems Using Controller-Based Dynamic Linearization Method. - Xian Yu; Tianshi Chen 001 (IEEE Trans. Cybern., 2024)

A Family of Hyperparameter Estimators Linking EB and SURE for Kernel-Based Regularization Methods. - Meng Zhang; Tianshi Chen 001; Biqiang Mu (IEEE Trans. Autom. Control., 2024)

Parameterized gain-constrained Kalman Filtering via singular value decomposition. - Chenxiao Wang; Fuxing Yao; Tianshi Chen 001; Wei Xing Zheng 001; Guangren Duan 001; He Kong (Autom., 2025)

On kernel design for regularized Volterra series identification of Wiener-Hammerstein systems. - Yu Xu; Biqiang Mu; Tianshi Chen 001 (Autom., 2025)

Numerically Efficient and Stable Algorithms for Kernel-Based Regularized System Identification Using Givens-Vector Representation. - Zhuohua Shen; Junpeng Zhang; Martin S. Andersen 001; Tianshi Chen 001 (CoRR, 2025)