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20242026
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eess.SY2026

Data-Driven Tensor Decomposition Identification of Homogeneous Polynomial Dynamical Systems

Xin Mao, Joshua Pickard, Can Chen

Homogeneous polynomial dynamical systems (HPDSs), which can be equivalently represented by tensors, are essential for modeling higher-order networked systems, including ecological…

eess.SY2026

Maximum-Entropy Random Walks on Hypergraphs

Anqi Dong, Anzhi Sheng, Xin Mao +1

Random walks are fundamental tools for analyzing complex networked systems, including social networks, biological systems, and communication infrastructures. While classical random…

eess.SY2025

Data-driven model order reduction for T-Product-Based dynamical systems

Shenghan Mei, Ziqin He, Yidan Mei +4

Model order reduction plays a crucial role in simplifying complex systems while preserving their essential dynamic characteristics, making it an invaluable tool in a wide range of…

eess.SY2025

Data-driven Control of T-Product-based Dynamical Systems

Ziqin He, Yidan Mei, Shenghan Mei +4

Data-driven control is a powerful tool that enables the design and implementation of control strategies directly from data without explicitly identifying the underlying system dyna…

eess.SY2024

Data-driven Analysis of T-Product-based Dynamical Systems

Xin Mao, Anqi Dong, Ziqin He +2

A wide variety of data can be represented using third-order tensors, spanning applications in chemometrics, psychometrics, and image processing. However, traditional data-driven fr…

eess.SY2024

Controllability and Observability of Temporal Hypergraphs

Anqi Dong, Xin Mao, Can Chen

Numerous complex systems, such as those arisen in ecological networks, genomic contact networks, and social networks, exhibit higher-order and time-varying characteristics, which c…