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RISS 인기검색어
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- 저자 : Yinjing Guo (검색결과 4 건)
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EEG-based Safety Driving Performance Estimation and Alertness Using Support Vector Machine
Hongyu Sun,Lijun Bi,Bisheng Chen,Yinjing Guo 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.6
Safety driving performance estimation and alertness (SDPEA) has drawn the attention of researchers in preventing traffic accidents caused by drowsiness while driving. Psychophysiological measures, such as electroencephalogram (EEG), are accurately investigated to be robust candidates for drivers’ drowsiness evaluation. This paper presents an effective EEG-based driver drowsiness monitoring system by analyzing the changes of brain activities in a simulator driving environment. The proposed SDPEA system can translate EEG signals into drowsiness level. Firstly, Independent component analysis (ICA) is performed on EEG data to remove artifacts. Then, eight EEG-band powers- related features: beta, alpha, theta, delta, (alpha plus theta)/beta, alpha / beta, (alpha plus theta)/(alpha plus beta) and theta / beta are extracted from the preprocessed EEG signals by employing the Fast Fourier Transform (FFT). Subsequently, fisher score technique selects the most descriptive features for further classification. Finally, Support Vector Machine (SVM) is employed as a classifier to distinguish drowsiness level. Experimental results show that the quantitative driving performance can be correctly estimated through analyzing driver’s EEG signals by the SDPEA system.
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An LDPC-COFDM based High Speed Mobile Wireless Communication System
Hongyu Sun,Lijun Bi,Xiang Lu,Yinjing Guo 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12
Coded Orthogonal Frequency Division Multiplexing (COFDM) is very well matched to the terrestrial channel, being able to cope with severe multi-path and the presence of co-channel narrowband interference. This paper presents an image and video transmission scheme based on COFDM for high speed mobile wireless communication system in which a good Rate-Compatible Low-Density Parity-Check codes structure is applied, this structure can provide a large range of supporting rates, and provide very good error performance, low decoding latency and low computational complexity at the decoder. The test experiment was made in television live transmitting to validate the designed system. The results show that our COFDM-based mobile wireless digital multimedia broadcasting system can transmit high definition image and video when it being equipped for 486Kilometre/Hour’s high speed rail, The Channel Bit Error Rate <2.0E-4 and Carrier to noise ratio(C/N) >30dB when the output power at 30dBm.
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Dynamic Event-triggered Quantitative Feedback Control for Switched Affine Systems
Xiang Lu,Hongyu Sun,Xinzheng Lyu,Anhao Wen,Yinjing Guo,Gang Jing,Qunxian Zheng 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.6
This paper focuses on the design of a dynamic output feedback controller for switched affine systems under limited communication resources. Since the system states information is difficult to obtain, the dynamic output feedback switching function is considered to stabilize the switched affine system. Quantized output measurements are transmitted to the dynamic output feedback controller to reduce the communication load. In order to significantly reduce the sampling frequency, an event-triggering mechanism is introduced to detect the event periodically. By using Lyapunov stability theory and linear matrix inequality (LMI) technique, a set of dynamic output feedback gains together with a switching rule are designed assuring the global asymptotic stability of the desired equilibrium point. More specifically, the design conditions do not require that there exist a stable convex combination of the subsystems state-space matrix. Finally, a numerical example show the validity of the obtained results of this paper.
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CSI-based human sensing using model-based approaches: a survey
Zhengjie Wang,Zehua Huang,Chengming Zhang,Wenwen Dou,Yinjing Guo,Da Chen 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.2
Currently, human sensing draws much attention in the field of ubiquitous computing, and human sensing based on WiFi CSI (channel state information) becomes a hot research topic due to the easy deployment and availability of WiFi devices. Although various human sensing applications based on the CSI signal model are emerging, the model-based approach has not been studied thoroughly. This paper provides a comprehensive survey of the latest model-based human sensing methods and their applications. First, the CSI signal and framework of model-based human sensing methods are introduced. Then, related models and fundamental signal preprocessing techniques are described. Next, typical human sensing applications are investigated, and the crucial characteristics are summarized. Finally, the advantages, limitations, and future research trends of model-based human sensing methods are concluded in this paper.
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