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Secrecy performance analysis of single-input multiple-output generalized-K fading channels

Frontiers of information Technology and Electronic Engineering 2016年第10期17卷 1074-1084页

作者： Lei, Hong-jiang Ansari, Imran Shafique Gao, Chao Guo, Yong-cai Pan, Gao-feng Qaraqe, Khalid A. Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China MOE Key Laboratory of Optoelectronic Technology and Systems Chongqing University Chongqing400044 China Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China

In this paper, the transmission of confidential messages through single-input multiple-output (SIMO) independent and identically generalized-K (KG) fading channels is considered, where the eavesdropper overhears the transmission from the transmitter to the receiver. Both the receiver and the eavesdropper are equipped with multiple antennas, and both active and passive eavesdroppings are considered where the channel state information of the eavesdropper’s channel is or is not available at the transmitter. The secrecy performance of SIMO KG systems is investigated. Analytical expressions for secrecy outage probability and average secrecy capacity of SIMO systems are derived via two different methods, in which KG distribution is approximated by the Gamma and mixture Gamma distributions, respectively. Numerical results are presented and verified via the Monte-Carlo simulation. © 2016, Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg.

关键词： Fading channels

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Effects of Acute Moderate Intensity Exercise on the EEGFrontal Alpha Asymmetry 4

Effects of Acute Moderate Intensity Exercise on the EEGFront...

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2019 4th International Seminar on Computer Technology, Mechanical and Electrical Engineering, ISCME 2019

作者： Xiao, Zhangyan Long, Zhengji Gao, Pengfei Qin, Chaoling Liu, Guangyuan College of Electronic Information and Engineering Southwest University Chongqing China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China College of Physical Education Southwest University Chongqing China

Exercise can improve physical and psychological states efficiently. Previous studies have shown that the frontal alpha asymmetry can be used to express emotional states, while relative activity in the larger left frontal can predict positive effects. In this study, our purpose is to observe the effects of pedalling exercise (PE) on the frontal alpha asymmetry during negative stimulation. The electroence phalograph (EEG)signals obtained are processed by matlab to obtain the frontal asymmetry value. By observing and comparing the frontal alpha asymmetry between two groups, we can find that the frontal alpha asymmetry of the sports group increased significantly, while the control group have no significantly change. The study shows that the acute moderate intensity PE can improve the resistance to negative stimuli and increase positive emotions. © Published under licence by IOP Publishing Ltd.

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Tracking control with event-triggered strategy for multi-agent systems with noises

Tracking control with event-triggered strategy for multi-age...

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作者： Tang, Zhaojun Li, Chuandong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Department of Electronics and Information Engineering Southwest University Chongqing400715 China School of Science Chongqing University of Technology Chongqing400054 China

This paper is concerned with a tracking control problem of multi-agent systems with noises. It is assumed that each agent in the network updates its state only at some discrete time instants, which determined by the event-triggered condition, and the agents are affected by noises. In order to attenuate the effect of noises, consensus-gain function is introduced in the control protocol. Centralized and decentralized event-triggered protocols are proposed to ensure that the followers track the considered leader. With the help of matrix theory and Lyapunov method, sufficient conditions are derived to solve the mean square tracking control. Simulation results are provided to illustrate the theoretical results. © 2018 John Wiley & Sons, Ltd.

关键词： Multi agent systems

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Impact of Crosstalk and Loss on the Training Process of Integrated Photonic Neural Networks 6

Impact of Crosstalk and Loss on the Training Process of Inte...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Pang, Jing Su, Ye Xie, Yiyuan College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing Chongqing400715 China

ISBN: (纸本)9798350353594

Integrated photonic neural networks (IPNNs), with their ability to process large-scale data and parallelize multiple computational tasks, have shown impressive promise for applications in the field of artificial intelligence. However, due to some hard-to-ignore non-ideal characteristics of the underlying silicon photonic MZI devices constituting the IPNN, these non-ideal characteristics can cause the input signal to be affected by crosstalk noise and optical loss during transmission, thus affecting the training and inference accuracy of the IPNN. In order to solve these problems, this paper establishes an analytical model of IPNN affected by crosstalk noise and loss during the training process, covering component level, layer level and system level. Simulations using this model show that the inference accuracy of IPNN decreases by about 65% when the crosstalk noise in the training phase of IPNN reaches -20 dB, while the inference accuracy of IPNN decreases by about 55% when the optical loss reaches -0.5 dB. © 2024 IEEE.

关键词： Crosstalk

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Distributed Model Predictive Control Framework for Consensus of Multi-Agent System 20

Distributed Model Predictive Control Framework for Consensus...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Li, Huaqing Zheng, Lifeng Wang, Huiwei Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering No. 2 Tiansheng Road Beibei District Chongqing China

ISBN: (纸本)9798350320831

Considering the widespread applications of the model predictive control (MPC), such as industrial process control and robotic operations, this paper proposes an MPC-based asynchronous distributed algorithm to solve the consensus problem of multi-agent system (MAS) by using the operator splitting method. The proposed algorithm is asynchronous, which means that all agents do not require to update and communicate simultaneously. When the positive uncoordinated step sizes satisfy the given condition, the optimal solution can be worked out by using the proposed algorithm. Moreover, all agents are allowed to set the step sizes locally based on local information. Numerical simulation validates the feasibility and effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Model predictive control

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Efficient regulation of emotion by positive music based on EEG valence-arousal model 2021

Efficient regulation of emotion by positive music based on E...

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3rd International Conference on Image, Video and Signal processing, IVSP 2021

作者： Zhou, Wei Qiu, Chenyang Liu, Guangyuan Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing China Neuroscience and Intelligent Media Institute Communication University of China Beijing China

ISBN: (纸本)9781450388917

Emotional regulation plays an important role in the process of affective computing and interactive system. Although studies have confirmed that music can be used as an effective medium for regulating emotions, it does not explain the effects of regulation from different dimensions of emotions. In this study, we collected electroencephalogram (EEG) data of 40 participants while regulating negative emotions by positive music. A valence-arousal model was trained on EEG features through machine learning. The model provided a binary prediction of valence (high or low) of 78.759.48% and 73.985.54% for arousal. Our results confirmed the function of positive music in emotion improvement. More attention should be paid to the value of music in emotional regulation arousal in clinical practice. © 2021 ACM.

关键词： Electroencephalography

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High Contrast Ratio 4-to-2 Plasmonic Encoder Utilizing Cascaded Ring Resonators 6

High Contrast Ratio 4-to-2 Plasmonic Encoder Utilizing Casca...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Chen, Yan Xie, Yiyuan Chai, Junxiong Ye, Yichen College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing Chongqing400715 China

ISBN: (纸本)9798350353594

In this paper, a novel plasmonic 4-to-2 encoder comprising cascaded ring resonators coated with graphene layers and two metal-insulator-metal (MIM) waveguides. The encoding function operates at 850 nm by modulating the intensity of pump beam focused on the graphene layer to manipulate the state of the plasmonic resonators. The performance of the encoder is analyzed utilizing the finite-difference time-domain method, demonstrating a high contrast ratio of 15.1 dB. Thus, this efficient 4-to-2 optical encoder is well-suited for integration into optical integrated computing devices. © 2024 IEEE.

关键词： Semiconductor insulator boundaries

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Remote Detection and Classification of Human Stress Using a Depth Sensing Technique

Remote Detection and Classification of Human Stress Using a ...

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Asian Conference on Affective Computing and intelligent Interaction (ACII Asia)

作者： Yuhao Shan Tong Chen Liansheng Yao Zhan Wu Wanhui Wen Guangyuan Liu Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing Southwest University Chongqing China

ISBN: (纸本)9781538653128

Stress plays an important role in our daily life. Long-term's psychological stress will lead to serious health as well as social problems, it is important to detect and monitor the psychological stress in its early stage. Most existing stress detection equipment are contact-type, such as wrist strap. However, in a real application, such as a working environment, a contact-free stress detection system will bring greater convenience. In this paper, we proposed a novel framework for detecting and classifying human stress based on respiratory signals measured remotely by using a Kinect sensor with a detection range of 3 meters. We test the framework on respiratory signals data set from 20 individuals under 3 different tasks (listen relax music, do exercise and do Stroop Color-word test), corresponding to relaxation, physical stress and psychological stress state. Experimental results suggest that the proposed method is a promising way for monitoring human stress and even discriminating psychological stress from the physical stress.

关键词： human computer interaction medical signal processing patient monitoring psychology medical signal processing computer human interaction Psychological Stress Patient Monitoring Psychology Stress (mechanics) physical stress strapping of wrist Stressing telemetry Sensing Techniques Social Problems

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Infant Facial Expression Analysis towards Defecation Detection 4

Infant Facial Expression Analysis towards Defecation Detecti...

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4th IEEE International Conference on Electronics Technology, ICET 2021

作者： Liu, Shihan Liu, Xinyu Chen, Tong Jiang, Ziyu Southwest University School of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Chongqing China Southwest University School of Electronic and Information Engineering Chongqing China

ISBN: (纸本)9781728176734

Infants need constant care from parents or caregivers, and cannot express themselves verbally. Therefore, automatic infant facial expression recognition system plays an important role in reducing the care burden. As a non-negligible part of baby care, automatic defecation detection based on infant facial expressions has not been investigated yet. This detection is especially important for young parents with little caring experience. In this paper, we built an Infant Expression Database of 465 images from 419 infants, including four categories: happiness, pain, defecation and sleep. Based on this database, we proposed a shallow network structure containing only three convolutional layers for infant facial expression recognition, which achieved an average accuracy of 84.93% for these four categories. Moreover, the recognition results showed that the network has a strong generalization ability, with 81.82% detection accuracy of infant defecation. © 2021 IEEE.

关键词： Face recognition

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Facial StO2: A New Promising Biometric Identity

Facial StO2: A New Promising Biometric Identity

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Peng, Dairong Sun, Sirui Liu, Xinyu Zhou, Ju Chen, Tong Institute of Legal Psychology and Intelligent Computing Southwest University Chongqing400715 China Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Chongqing400715 China Southwest University School of Electronic and Information Engineering Chongqing400715 China

ISBN: (纸本)9781665468190

In this paper, we introduce a new biometric identity, facial tissue oxygen saturation (StO2). StO2 is an index of blood oxygen content in tissues and is related to blood vessel distribution pattern and metabolic rate. Experimental results show that classification accuracy can reach 83.33% in 42 participants with different stress states by using StO2 as the only input to the ResNet-50 model. We also proposed a module called StO2Net to eliminate the effects of stress on classification. The highest accuracy can reach up to 90.48% when the module is used. This pilot study shows that facial StO2 can be a promising biometric feature for identity recognition. © 2022 IEEE.

关键词： Biometrics

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