A5016333163- Wireless Signal Modulation Classification
- Full-Duplex Wireless Communications
- Advanced SAR Imaging Techniques
- Indoor and Outdoor Localization Technologies
- Speech and Audio Processing
- Seed Germination and Physiology
- Cocoa and Sweet Potato Agronomy
- Radar Systems and Signal Processing
- Biometric Identification and Security
- Underwater Vehicles and Communication Systems
- Terahertz technology and applications
- Infant Health and Development
- Leaf Properties and Growth Measurement
- Plant Virus Research Studies
- Advanced Wireless Communication Techniques
- Error Correcting Code Techniques
- Digital Media Forensic Detection
- Organic Light-Emitting Diodes Research
- Target Tracking and Data Fusion in Sensor Networks
- Luminescence and Fluorescent Materials
- Molecular Sensors and Ion Detection
University of Science and Technology of China
2018-2024
China Academy of Space Technology
2024
Chinese Academy of Sciences
2018-2024
Landscape Institute
2023
Guizhou Institute of Technology
2017
Machine learning approaches are becoming increasingly popular to improve the efficiency of specific emitter identification (SEI). However, in most non-cooperative SEI scenarios, supervised and semi-supervised often incompatible due lack labeled datasets. To solve this challenge, an unsupervised framework is proposed based on information maximized generative adversarial networks (InfoGANs) radio frequency fingerprint embedding (RFFE). enhance individual discriminability, a gray histogram...
Specific emitter identification (SEI) enables the classification of various unique emitters based on received waveforms using some external feature measurements from their transmit signals and has shown its potential for military civil applications. However, characterization waveform is susceptible to factors in propagation process, resulting inaccurate representations individual emitters, so discriminative performances existing methods are usually challenging. To remedy these shortcomings,...
Wireless signal identification plays an important role in effectively implementing spectrum monitoring and management. However, ISM (Industrial, Science Medical) band, it becomes a challenging task due to the heterogeneity of variously emerging wireless techniques, part potential unknown spectral occupants may even hinder feasibility identification. To overcome such difficulties, we focus on open-set recognition (OSR) this paper present multi-task learning architecture based deep neural...
User location is important for network operators to perform the management and services. This paper considers problem of fingerprinting localization in LTE networks. Fingerprint information extracted from measurement reports (MRs) gathered at side. We present an Adaptive Forward (AFW) algorithm based on a hidden Markov model (HMM), where states are locations Equipments (UEs), observations Reference Signal Received Power (RSRP) vectors MRs. The transition probability HMM trained neighboring...
Abstract Litsea cubeba (Lour.) Pers. is an important spice plant in southern China. The whole of contains essential oils, among which the fruit has highest oil content. And there a significant market demand and widespread use fruit. However, are few systematic studies on growth development This study aims to determine regularity annual changes morphology, content, components optimal harvest period improve utilization efficiency resource. results show that change morphology was consistent...
Reliable information transmission in complex electromagnetic interference environments is an essential proposition for wireless communication systems. This paper proposes iterative structure single antenna receiver, which combines both blind signal extraction (BSE) and convolutional neural network (CNN) to mitigate potential co-channel (CCI) as well colored noise. Firstly, the channel received transformed into a multi-channel observations so that proposed can use BSE extract target signal....