3 citations · 4 across the 14 of their papers we have counts for
14 papers
Bayes Estimators with Performance Comparable to Empirical Bayes Estimators and Improved Local Robustness
Yue Ju, Ying Wang, Jiabao He +2
Bayes estimation has been extensively studied and widely used in statistics, decision theory, signal processing, machine learning, and system identification. Among its variants, em…
Fundamental Limitations of Data-Driven Control: A Statistical Decision Perspective
Jiabao He, Feiran Zhao, Yushan Li +3
Substantial research efforts have been devoted to the design of data-driven controllers; however, comparatively less is known about their statistical performance and fundamental li…
Preserving Topology Privacy of Network Systems by Feedback: Conditions and Distributed Design
Yushan Li, Jiabao He, Julien M. Hendrickx +1
This paper develops a feedback-based method to preserve the topology privacy of consensus protocols in network systems. The key idea is to intentionally violate topology identifiab…
Data-Driven Moving Horizon Estimators for Linear Systems with Sample Complexity Analysis
Peihu Duan, Jiabao He, Yuezu Lv +1
This paper investigates the state estimation problem for linear systems subject to Gaussian noise, where the model parameters are unknown. By formulating and solving an optimizatio…
Resistant Topology Inference in Consensus Networks: A Feedback-Based Design
Yushan Li, Jiabao He, Dimos V. Dimarogonas
Consensus networks are widely deployed in numerous civil and industrial applications. However, the process of reaching a common consensus among nodes can unintentionally reveal the…
Bridging the Prediction Error Method and Subspace Identification: A Weighted Null Space Fitting Method
Jiabao He, S. Joe Qin, Håkan Hjalmarsson
Subspace identification methods (SIMs) have proven to be very useful and numerically robust for building state-space models. While most SIMs are consistent, few if any can achieve…
Range Space or Null Space: Least-Squares Methods for the Realization Problem
Jiabao He, Yueyue Xu, Yue Ju +2
This contribution revisits the classical approximate realization problem, which involves determining matrices of a state-space model based on estimates of a truncated series of Mar…
Finite Sample Analysis of Open-loop Subspace Identification Methods
Jiabao He, Ingvar Ziemann, Cristian R. Rojas +2
Subspace identification methods (SIMs) are known for their simple parameterization for MIMO systems and robust numerical properties. However, a comprehensive statistical analysis o…
Weighted Null Space Fitting (WNSF): A Link between The Prediction Error Method and Subspace Identification
Jiabao He, S. Joe Qin, Håkan Hjalmarsson
Subspace identification methods (SIMs) have proven to be very useful and numerically robust for building state-space models. While most SIMs are consistent, few if any can achieve…
A Weighted Least-Squares Method for Non-Asymptotic Identification of Markov Parameters from Multiple Trajectories
Jiabao He, Cristian R. Rojas, Håkan Hjalmarsson
Markov parameters play a key role in system identification. There exists many algorithms where these parameters are estimated using least-squares in a first, pre-processing, step,…
Weighted Least-Squares PARSIM
Jiabao He, Cristian R. Rojas, Håkan Hjalmarsson
Subspace identification methods (SIMs) have proven very powerful for estimating linear state-space models. To overcome the deficiencies of classical SIMs, a significant number of a…
Finite Sample Analysis for a Class of Subspace Identification Methods
Jiabao He, Ingvar Ziemann, Cristian R. Rojas +1
While subspace identification methods (SIMs) are appealing due to their simple parameterization for MIMO systems and robust numerical realizations, a comprehensive statistical anal…
Data-Driven Robust Control for Discrete Linear Time-Invariant Systems: A Descriptor System Approach
Jiabao He, Xuan Zhang, Feng Xu +2
Given the recent surge of interest in data-driven control, this paper proposes a two-step method to study robust data-driven control for a parameter-unknown linear time-invariant (…
Data-Driven Controllability Analysis and Stabilization for Linear Descriptor Systems
Jiabao He, Xuan Zhang, Feng Xu +2
For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it. First, a data-b…