7 papers
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…
Structural Controllability of Large-Scale Hypergraphs
Joshua Pickard, Xin Mao, Can Chen
Controlling real-world networked systems, including ecological, biomedical, and engineered networks that exhibit higher-order interactions, remains challenging due to inherent nonl…
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…
Model Reduction of Homogeneous Polynomial Dynamical Systems via Tensor Decomposition
Xin Mao, Can Chen
Model reduction plays a critical role in system control, with established methods such as balanced truncation widely used for linear systems. However, extending these methods to no…
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…
Tensor-based homogeneous polynomial dynamical system analysis from data
Xin Mao, Anqi Dong, Ziqin He +3
Numerous complex real-world systems, such as those in biological, ecological, and social networks, exhibit higher-order interactions that are often modeled using polynomial dynamic…