Tianshi Chen

发表

Decentralized Particle Filter With Arbitrary State Decomposition

Henrik Ohlsson, Lennart Ljung, Thomas B. Schön, 2011, IEEE Transactions on Signal Processing.

On the estimation of transfer functions, regularizations and Gaussian processes - Revisited

Henrik Ohlsson, Lennart Ljung, Tianshi Chen, 2012, Autom..

Constructive state space model induced kernels for regularized system identification

L. Ljung, Tianshi Chen, 2014 .

On the Estimation of Transfer Functions, Regularizations and Gaussian Processes – Revisited

L. Ljung, Tianshi Chen, Henrik Ohlsson, 2011 .

On kernel structures for regularized system identification (II): a system theory perspective

L. Ljung, Tianshi Chen, 2015 .

A shift in paradigm for system identification

Tianshi Chen, Lennart Ljung, Biqiang Mu, 2019, Int. J. Control.

Regularization Features in the System Identification Toolbox

L. Ljung, Tianshi Chen, Rajiv Singh, 2015 .

On Asymptotic Properties of Hyperparameter Estimators for Kernel-based Regularization Methods pdf

Lennart Ljung, Tianshi Chen, Bi-Qiang Mu, 2017, Autom..

Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, 53rd IEEE Conference on Decision and Control.

What Can Regularization Offer for Estimation of Dynamical Systems?

Lennart Ljung, Tianshi Chen, L. Ljung, 2013, ALCOSP.

Regularized system identification using orthonormal basis functions

Lennart Ljung, Tianshi Chen, L. Ljung, 2015, 2015 European Control Conference (ECC).

Asymptotic Properties of Generalized Cross Validation Estimators for Regularized System Identification

L. Ljung, Tianshi Chen, Bi-Qiang Mu, 2018 .

Impulse Response Estimation with Binary Measurements: A Regularized FIR Model Approach

L. Ljung, Tianshi Chen, Yanlong Zhao, 2012 .

On kernel structures for regularized system identification (I): a machine learning perspective

L. Ljung, Tianshi Chen, 2015 .

J ul 2 01 7 OnAsymptoticProperties ofHyperparameterEstimators for Kernel-basedRegularizationMethods ⋆

L. Ljung, Tianshi Chen, BiqiangMu, 2018 .

Kalman filtering under unknown inputs and norm constraints

Mao Shan, Salah Sukkarieh, Wei Xing Zheng, 2021, Autom..

On Embeddings and Inverse Embeddings of Input Design for Regularized System Identification

Tianshi Chen, He Kong, Junfeng Wu, 2022, Autom..

An Efficient Implementation for Spatial-Temporal Gaussian Process Regression and Its Applications

Tianshi Chen, Renxin Zhong, Biqiang Mu, 2022, Autom..

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyper-parameter Estimator

L. Ljung, Tianshi Chen, Biqiang Mu, 2022, 2209.12231.

On Kernel Design for Non-Causal Systems with Application to Feedforward Control

Tianshi Chen, Xiaozhu Fang, 2022, 2022 41st Chinese Control Conference (CCC).

On Kernel Design for Regularized Volterra Series Model with Application to Wiener System Identification

Tianshi Chen, Biqiang Mu, Yu Xu, 2022, 2022 41st Chinese Control Conference (CCC).

On Asymptotic Distribution of Generalized Cross Validation Hyper-parameter Estimator for Regularized System Identification*

L. Ljung, Tianshi Chen, Biqiang Mu, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Identifiability Analysis of Noise Covariances for LTI Stochastic Systems With Unknown Inputs

Tianshi Chen, S. Sukkarieh, He Kong, 2022, IEEE Transactions on Automatic Control.

Global robust stabilization of feedforward systems with uncertainties

Tianshi Chen, Jie Huang, 2010 .

On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses

Tianshi Chen, Gianluigi Pillonetto, Tianshi Chen, 2018, Autom..

On kernel design for regularized LTI system identification pdf

Tianshi Chen, Tianshi Chen, 2016, Autom..

Maximum Entropy Kernels for System Identification

Francesca P. Carli, Tianshi Chen, L. Ljung, 2014, IEEE Transactions on Automatic Control.

Kernel methods in system identification, machine learning and function estimation: A survey

Lennart Ljung, Tianshi Chen, Giuseppe De Nicolao, 2014, Autom..

Implementation of algorithms for tuning parameters in regularized least squares problems in system identification

Lennart Ljung, Tianshi Chen, L. Ljung, 2013, Autom..

Convexity issues in system identification

Lennart Ljung, Tianshi Chen, L. Ljung, 2013, 2013 10th IEEE International Conference on Control and Automation (ICCA).

Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint pdf

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2015, Autom..

Robust Gaussian process regression with G-confluent likelihood

C. A. Naesseth, Tianshi Chen, Martin Lindfors, 2020 .

Cramér–Rao Bounds for Filtering Based on Gaussian Process State-Space Models

Feng Yin, Yuxin Zhao, Gustaf Hendeby, 2019, IEEE Transactions on Signal Processing.

On the Asymptotic Optimality of Cross-Validation based Hyper-parameter Estimators for Regularized Least Squares Regression Problems

Lennart Ljung, Tianshi Chen, Biqiang Mu, 2021, 2104.10471.

Transfer function and transient estimation by Gaussian process regression in the frequency domain

Tianshi Chen, John Lataire, Tianshi Chen, 2016, Autom..

System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, IEEE Transactions on Automatic Control.

Global Robust Output Regulation by State Feedback for Strict Feedforward Systems

Jie Huang, Tianshi Chen, Tianshi Chen, 2009, IEEE Transactions on Automatic Control.

Global robust output regulation of nonlinear strict feedforward systems

Jie Huang, Tianshi Chen, Tianshi Chen, 2008 .

Kernel-based model order selection for identification and prediction of linear dynamic systems

Lennart Ljung, Tianshi Chen, Gianluigi Pillonetto, 2013, 52nd IEEE Conference on Decision and Control.

Regularized LTI system identification in the presence of outliers: A variational EM approach

Tianshi Chen, Martin Lindfors, Tianshi Chen, 2020, Autom..

Continuous-time DC kernel — A stable generalized first order spline kernel

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Kernel selection in linear system identification part II: A classical perspective

Henrik Ohlsson, Lennart Ljung, Graham C. Goodwin, 2011, IEEE Conference on Decision and Control and European Control Conference.

Maximum entropy property of discrete-time stable spline kernel

Tianshi Chen, Tohid Ardeshiri, Tianshi Chen, 2014, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Regularized System Identification

L. Ljung, Tianshi Chen, G. Pillonetto, 2022, Communications and Control Engineering.

Spectral analysis of the DC kernel for regularized system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

Continuous-Time DC Kernel—A Stable Generalized First-Order Spline Kernel

Tianshi Chen, Tianshi Chen, 2018, IEEE Transactions on Automatic Control.

Multiple Kernel Based Regularized System Identification with SURE Hyper-parameter Estimator

Tianshi Chen, Martin S. Andersen, Biqiang Mu, 2018 .

On Input Design for Regularized LTI System Identification: Power-constrained Input

Tianshi Chen, Bi-Qiang Mu, Tianshi Chen, 2017, Autom..

Scalable anomaly detection in large homogeneous populations

Henrik Ohlsson, Lennart Ljung, Tianshi Chen, 2013, Autom..

Accelerated Sparse Bayesian Learning via Screening Test and Its Applications pdf

Tianshi Chen, Yiping Jiang, Tianshi Chen, 2020, ArXiv.

Asymptotic Properties of Hyperparameter Estimators by Using Cross-Validations for Regularized System Identification

Lennart Ljung, Tianshi Chen, Bi-Qiang Mu, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Regularized LTI System Identification with Multiple Regularization Matrix

Lennart Ljung, S. Joe Qin, Tianshi Chen, 2018 .

A small gain approach to global stabilization of nonlinear feedforward systems with input unmodeled dynamics

Jie Huang, Tianshi Chen, Tianshi Chen, 2010, Autom..

Decentralization of particle filters using arbitrary state decomposition

Henrik Ohlsson, Lennart Ljung, Tianshi Chen, 2010, 49th IEEE Conference on Decision and Control (CDC).

Input Design for Regularized System Identification: Stationary Conditions and Sphere Preserving Algorithm

Tianshi Chen, He Kong, Junfeng Wu, 2023, IEEE Transactions on Automatic Control.

Persistence of excitation for identifying switched linear systems

E. Bai, Tianshi Chen, Changming Cheng, 2022, Autom..

Identification of Switched Linear Systems: Persistence of Excitation and Numerical Algorithms pdf

Er-Wei Bai, Changming Cheng, Biqiang Mu, 2021, ArXiv.

Model Error Modeling and Stochastic Embedding

Lennart Ljung, Graham C. Goodwin, Juan C. Agüero, 2015 .

On Kernel Design for Regularized Non-Causal System Identification

Tianshi Chen, Xiaozhu Fang, 2023, Automatica.

Kernel-based Regularized Iterative Learning Control of Repetitive Linear Time-varying Systems

Tianshi Chen, Xiaozhu Fang, Xian Yu, 2023, Autom..

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyperparameter Estimator

L. Ljung, Tianshi Chen, Biqiang Mu, 2022, IEEE Transactions on Automatic Control.

Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model

L. Ljung, Tianshi Chen, Biqiang Mu, 2021, ArXiv.

On semiseparable kernels and efficient implementation for regularized system identification and function estimation

Martin S. Andersen, Tianshi Chen, Tianshi Chen, 2021, Autom..

On the Influence of Ill-conditioned Regression Matrix on Hyper-parameter Estimators for Kernel-based Regularization Methods*

Lennart Ljung, Tianshi Chen, Biqiang Mu, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

On Effects of Condition Number of Regression Matrix upon Hyper-parameter Estimators for Kernel-based Regularization Methods

Lennart Ljung, Tianshi Chen, Yue Ju, 2020, ArXiv.

Supplementary Material for CDC Submission No. 1461

L. Ljung, Tianshi Chen, Biqiang Mu, 2020, 2003.13435.

On the input design for kernel-based regularized LTI system identification: Power-constrained inputs

Lennart Ljung, Tianshi Chen, Bi-Qiang Mu, 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

Maximum entropy properties of discrete-time first-order stable spline kernel

Lennart Ljung, Francesca P. Carli, Tianshi Chen, 2014, Autom..

Regularization strategies for nonparametric system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2013, 52nd IEEE Conference on Decision and Control.

Sparse multiple kernels for impulse response estimation with majorization minimization algorithms

Lennart Ljung, Francesca P. Carli, Tianshi Chen, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels

Lennart Ljung, Tianshi Chen, Ruggero Carli, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

On the estimation of transfer functions, regularizations and Gaussian processes - Revisited

L. Ljung, Tianshi Chen, Henrik Ohlsson, 2012, Autom..

Comments on "State estimation for linear systems with state equality constraints" [Automatica 43 (2007) 1363-1368]

Tianshi Chen, Tianshi Chen, 2010, Autom..

The noise covariances of linear Gaussian systems with unknown inputs are not uniquely identifiable using autocovariance least-squares

Tianshi Chen, S. Sukkarieh, He Kong, 2022, Syst. Control. Lett..

On the design of multiple kernels for nonparametric linear system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, 53rd IEEE Conference on Decision and Control.

Rank-1 kernels for regularized system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2013, 52nd IEEE Conference on Decision and Control.

Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series

Tianshi Chen, Z. Luo, S. Theodoridis, 2019, IEEE Transactions on Signal Processing.

Recursive Implementation of Gaussian Process Regression for Spatial-Temporal Data Modeling

Feng Yin, Tianshi Chen, Ye Kuang, 2019, 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP).