Portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in Communications in Nonlinear Science and Numerical Simulation, 2022
Recommended citation: Zehui Xiao, Zhenyu Wu, Jie Tao, "Asynchronous filtering for Markov jump systems within finite time: A general event-triggered communication; Communications in Nonlinear Science and Numerical Simulation, 2022.
Published in Applied Mathematics and Computation, 2022
Use Google Scholar for full citation
Recommended citation: Zhenyu Wu, Jiawei Chen, Xuexi Zhang, Zehui Xiao, Jie Tao, Xiaofeng Wang, "Dynamic event-triggered synchronization of complex networks with switching topologies: Asynchronous observer-based case." Applied Mathematics and Computation, 2022.
Published in Nonlinear Dynamics, 2023
Recommended citation: Zhenyu Wu, Zehui Xiao, Xuexi Zhang, Jie Tao, "Event-Triggered quasi-synchronization of neural networks with hidden Markov model-based asynchronous target." Nonlinear Dynamics, 2023.
Published in IEEE Transactions on Neural Networks and Learning Systems, 2023
Recommended citation: Jie Tao; Zhenyu Wu; Zehui Xiao; Hongxia Rao; Yong Xu; Peng Shi; Synchronization of Markov Jump Neural Networks With Communication Constraints via Asynchronous Output Feedback Control; IEEE Transactions on Neural Networks and Learning Systems, 2024.
Published in Information Sciences, 2023
Recommended citation: Zhenyu Wu; Jieren Pei; Xuexi Zhang; Jie Tao; Renquan Lu;Fuzzy adaptive event-triggered synchronization of complex dynamical networks via switched pinning control; Information Sciences, 2023.
Published in Information Sciences, 2024
Recommended citation: Hekai Feng; Zhenyu Wu; Xuexi Zhang; Zehui Xiao; Meng Zhang; Jie Tao; Secure adaptive event-triggered anti-synchronization for BAM neural networks with energy-limited DoS attacks; Information Sciences, 2024.
Published in IEEE Transactions on Consumer Electronics (Now is Minor Revision), 2024
This paper proposes a super-resolution strategy for mmWave radar. Using the matrix-pencil method, principal component analysis is explored.
Recommended citation:
Download Paper | Download Slides
Published in IEEE Transactions on Consumer Electronics (Now is Major Revision), 2024
This paper addresses the super-resolution challenge in range and angle estimation for mmWave FMCW radar. It introduces a Modified Diagonal Loading (MDL) method to enhance the Iterative Adaptive Approach (IAA) for range estimation, especially in low SNR scenarios. The method adjusts dynamically based on noise levels, outperforming traditional techniques. A coherent extension technique is then applied to correct phase discontinuities across chirps, enabling longer signal construction for super-resolution range-angle mapping. Practical examples showcase its potential for high-precision point clouds, making it suitable for automotive radar and consumer IoT applications.
Published:
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.