A5101909779- Blind Source Separation Techniques
- Speech and Audio Processing
- Advanced Fiber Optic Sensors
- Force Microscopy Techniques and Applications
- Neural Networks and Reservoir Computing
- Advanced Memory and Neural Computing
- Nonlinear Optical Materials Studies
- Digital Media Forensic Detection
- Nonlinear Optical Materials Research
- Optical Network Technologies
University of Electronic Science and Technology of China
2023-2024
Hong Kong University of Science and Technology
2002
Fiber-optic distributed acoustic sensor (DAS) has been applied to various large-scale infrastructure monitoring areas in smart cities, leading a new generation of fiber-optic Internet Things for ground listening. However, its single-source detection and recognition methods may fail unpredictable multi-source interfering environments urban. When an unknown number sources are nonlinearly mixed at the DAS's fiber receiver, it increases difficulty multiple source separation further. Therefore,...
A novel blind source feature extraction method with dual-LSTM is proposed for DAS used in complicated ground burying environments. The results demonstrate the ability to accurately extract interested target signal unknown mixing
Summary form only given.We report here the realization of large third-order nonlinear susceptibility, /spl xi//sup (3)/, from Au:dielectric (SiO/sub 2/ and TiO/sub 2/) composite films near Au percolation threshold. The were prepared by co-sputtering onto a fused silica substrate. wavelength dependence (3)/ was measured degenerate four-wave mixing (DFWM) scheme, its enhancement studied time-resolved measurements.