Lihua Xie
Nanyang Technological University
1142 Papers
6.1K Citations
Lihua Xie is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Computer science & Linear system. The author has an hindex of 90, co-authored 1056 publications. Previous affiliations of Lihua Xie include Fuzhou University & Data Storage Institute.
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Papers
ResFi: WiFi-Enabled Device-Free Respiration Detection Based on Deep Learning
Jiaxing Hu,Jianfei Yang,Jenn-Bing Ong,Dazhuo Wang,Lihua Xie +4 more
- 27 Jun 2022
TL;DR: A device-free respiration detection system, ResFi, utilizing the CSI data from COTS WiFi devices is proposed, which shows an accuracy up to 15% higher than that of the traditional machine-learning methods.
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Auto-tuning of cascade control systems
Sihai Song,Lihua Xie,Wenjian Cai +2 more
- 07 Nov 2002
TL;DR: In this paper, a model matching PID controller tuning method based on the Pade coefficient and Markov parameter approximation is proposed for the overall system performance, which can be directly integrated into commercially available industrial autotuning systems.
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Multiple Kernel Representation Learning for WiFi-Based Human Activity Recognition
Han Zou,Yuxun Zhou,Jianfei Yang,Weixi Gu,Lihua Xie,Costas J. Spanos +5 more
- 01 Dec 2017
TL;DR: A novel multiple kernel representation learning (MKRL) framework that automatically extracts and combines informative patterns from the Channel State Information (CSI) measurements and achieves a 98\% activity recognition accuracy.
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A Behavior-Based Mobile Robot Navigation Method with Deep Reinforcement Learning
Juncheng Li,Maopeng Ran,Han Wang,Lihua Xie +3 more
- 05 Feb 2021
TL;DR: Deep reinforcement learning-based mobile robot navigation has attracted some recent interest and in the single-agent case, a robot can learn to navigate autonomously without a map of the environment.
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3-D Distributed Localization With Mixed Local Relative Measurements
Xu Fang,Xiaolei Li,Lihua Xie +2 more
TL;DR: The main idea is to construct displacement constraints for the positions of the nodes by using mixed local relative measurements and a linear distributed localization algorithm is proposed for each free node to estimate its position by solving the displacement constraints.
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