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5th China Conference on intelligent Networked Things, CINT 2022

作者： Li, Hongfei Xu, Jing Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China

ISBN: (纸本)9789811989148

Underwater vehicle system, as a kind of special machine capable of underwater resource exploration, submarine pipeline maintenance, marine environment reconnaissance and submarine rescue, is a common tool in modern marine exploitation. Underwater vehicles play an important role in the survey and exploration of marine resource. The fault tolerant control for underwater vehicle system with external disturbance and actuator faults is studied in this paper. The fault observer can estimate the fault in the existence of disturbance environment. A sufficient condition for the existence of fault observer is proposed which guarantees the stability of the closed-loop system under actuator faults. Moreover, a fault-tolerant controller is developed to compensate for the failure effects on the system by updating the design feedback matrices online. For the fault-tolerant controller, Lyapunov function is used to obtain the stability for underwater vehicle system about actuator saturation. Finally, an example is included to show the effectiveness of the presented theory. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lyapunov functions

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TS-CAN+: A Improved TS-CAN Architecture for non-Contact Heart Rate Measurement

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IEEE Transactions on Consumer Electronics 2024年 1-1页

作者： Li, Yihang Huang, Junjian Zhao, Jichao Wu, Dayu Zheng, Mao Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China University of Auckland Auckland New Zealand

Heart rate is one of the most crucial physiological indicators of the human body, which can reflect the health status of the cardiovascular and cerebrovascular. Therefore, heart rate monitoring in real-time is essential for the prevention and treatment of cardiovascular and cerebrovascular diseases. Remote Photoplethysmography (rPPG) is a non-contact heart rate measurement method, which addresses the limitation of traditional heart rate measurement methods that need to contact with the subjects, and has a broad application prospect in ward vital signs monitoring and remote physiological health monitoring. How to use the rPPG method to measure heart rate more accurately is still a challenging problem. In this paper, we propose the TS-CAN+ method, which is based on TS-CAN and further incorporates convolutional block attention modules and replaces the ordinary convolution of the appearance branch with the depthwise separable convolution to improve the network accuracy. To validate the performance of our model, we conduct extensive experiments on the public PURE, UBFC-rPPG, and MMPD datasets. The experimental results indicate that compared with TS-CAN, the mean absolute error of TS-CAN+ is reduced by 37.21% in the cross-dataset test on UBFC-rPPG dataset and reduced by 12.18% on MMPD dataset. IEEE

关键词： Convolution

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Model-Free Reinforcement Learning Economic Dispatch Algorithms for Price-Based Residential Demand Response Management System

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 123-135页

作者： Li, Jun Li, Huaqing Huang, Tingwen Zheng, Lifeng Ji, Lianghao Yin, Shen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Mechanical and Industrial Engineering Faculty of Engineering Norwegian University of Science and Technology Trondheim7033 Norway

It is projected that plug-in electric vehicles (PEVs) would steadily increase as household appliances. However, PEVs’ high power consumption, stochastic usage patterns, and storage capacity will surely result in a rise in the elasticity of demand response and pose significant difficulties for price-based residential demand response management (PRDRM). This artcle aims to optimize a two-tier globally shared nonconvex PRDRM problem with local constraints and PEVs, known as social welfare: maximizing retailer profits and minimizing the combined residential costs. This is done by balancing residential electricity use with retail electricity prices in an unknown market environment. The proposed online/offline model-free reinforcement learning-based economic dispatch (MFRL-ED) methods can adaptively decide on the ideal retail price sequence by integrating the daily residential-retailer behavior model with the agent-environment interaction method, providing a basic MFRL-ED solution for PRDRM without a system identification step and an accurate load-retail model. Experiments show that MFRL-ED methods provide an effective class of PRDRM solutions. © 2023 Institute of Electrical and Electronics Engineers. All rights reserved.

关键词： Reinforcement learning

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Personality recognition based on ECG in response to VR emotional stimuli 23

Personality recognition based on ECG in response to VR emoti...

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3rd International Conference on Bioinformatics and intelligent Computing, BIC 2023

作者： Lan, Ping Xie, Jialan Hu, Zhaonian Liu, Guangyuan College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China Institute of Affective Computing and Information Processing Southwest University Chongqing400715 China Key Laboratory of Cognition and Personality Ministry of Education Faculty of Psychology Southwest University Chongqing400715 China

ISBN: (纸本)9798400700200

This paper explores the feasibility and effect of using ECG signals in response to virtual reality(VR) emotional stimuli for personality recognition. Personality represents an individual''s behavior pattern, so it has extensive research significance to identify personality. In the field of personality recognition, there have been researches on the use of physiological signals to recognize personality recently, but there have been no studies on personality recognition in VR scenarios. VR technology has been applied in many fields, and in the field of emotion recognition, the advantage of VR video as emotional arousal material has been proved. We designed the emotional stimulation experiment in VR scene to collect ECG signals, and constructed the personality recognition model. The results showed that the F1 scores of neuroticism, extraversion, openness, agreeableness and conscientiousness using only ECG were 0.79, 0.80, 0.81, 0.73 and 0.81, respectively, which were much higher than the random level. And we found that in VR scenes, negative emotional stimulation can achieve better personality recognition effect. Our results confirm the feasibility of personality recognition using ECG signals in response to VR emotional stimuli. © 2023 ACM.

关键词： Electrocardiograms

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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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Observer-Based Consensus of nonlinear Multi-Agent Systems With Input Delay via Delay-Dependent Event-Triggered Control

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 157-166页

作者： Wei Zhang Bingyan Gong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronics and Information Engineering Southwest University Chongqing China

The distributed control for leader-following consensus problem of nonlinear multi-agent systems with input delay is investigated in this paper. Based on observer state information, an improved distributed truncated prediction control strategy is proposed in order to address the issue of input delay. Furthermore, a delay-dependent event-triggered control protocol is designed to alleviate the use of computation resources and communication bandwidth. Unlike the existing event-triggered protocol, the protocol in the article is delay-dependent and specially designed for systems with input delay. Moreover, the Zeno behavior does not occur. It should be pointed out that, our observer-based control is significant for practical applications where the state of agents cannot be directly obtained. Utilizing the Lyapunov-Krasoviskii function theory, the sufficient conditions of the consensus under above two control methods are obtained. Lastly, we illustrate the feasibility of our results by illustrative examples.

关键词： Delays Protocols Observers Multi-agent systems linear matrix inequalities Sufficient conditions Cyber-physical systems

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Movie preference prediction based on EEG signal under high brain correlation 4

Movie preference prediction based on EEG signal under high b...

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4th International Conference on Signal processing and Computer Science, SPCS 2023

作者： Yue, Yuanhao Zhao, Xingcong Zhou, Wei Liu, Guangyuan School of Electronic and Information Engineering Southwest University Tiansheng Road Beibei Chongqing400715 China Institute of Affective Computing and Information Processing Southwest University Tiansheng Road Beibei Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Tiansheng Road Beibei Chongqing400715 China

ISBN: (纸本)9781510672505

In this study, we recorded the electroencephalography (EEG) of human subjects when they watched a movie trailer. Based on the willingness preference from the subjects after finished the movie trailer watching, the EEG signals were analyzed to build regression models to predict the subjects' movie preferences. We proposed a new approach to rise the prediction accuracy. Specifically, the correlated component analysis (CCA) algorithm was used to calculate the inter-subject correlation (ISC) of each time segment in the movie trailer and the ISC of each channel in the EEG. These two states were selected to locate the moment when a specific area of the brain responds most strongly to the video stimulation, as an effective indicator for predicting individual movie preferences. The experimental results show that the method of selecting effective EEG signals at the level of ISC has achieved a better prediction effect on the GBDT regression model (R2 = 0.733, RMSE = 0.681). We also found that low-frequency EEG signals in the θ and δ bands of the parietal and occipital sites are more effective in predicting movie preferences than high-frequency EEG signals. © 2023 SPIE.

关键词： Electroencephalography

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Centroid-Based Security Monitoring for Indoor Elderly Care with Millimeter Wave Radar

Centroid-Based Security Monitoring for Indoor Elderly Care w...

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第43届中国控制会议

作者： Chicheng Huang Chuandong Li Zelin Gao Zhenyu Wu Yawei Shi Huaqing Li College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The increasing use of millimeter wave radar for smart elderly care is due to its precision,privacy,and *** technology enables real-time monitoring of unexpected incidents,particularly falls among the elderly *** examining the relationship between cloud points and human centroids,this paper exploits the unique features of millimeter wave radar for personnel detection and human activity *** improved Kalman filter algorithm for centroid tracking has been *** effectively monitors the three-dimensional trajectory and velocity changes associated with various human ***,machine learning algorithms and neural networks are employed to classify these behaviors,including walking,sitting,and *** to conventional Kalman filtering,this approach effectively handles dispersion characteristics within point clouds,resulting in a smoother trajectory and more consistent *** method enables the recognition of abnormal activities of people indoors with a maximum classification accuracy of 93.02%.

关键词： Millimeter Wave Radar Point Clouds Centroid Tracking Human Activity Recognition

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Community Energy Management System Based on Deep Learning and Lagrangian Programming Neural Network

Community Energy Management System Based on Deep Learning an...

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Neuromorphic Computing (ICNC), International Conference on

作者： Shuying Xu Xing He Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9798331508661

ISBN: (纸本)9798331508678

In this paper, a innovative approach is proposed for solving the energy scheduling problem (ESP) in community energy management system (CEMS), combining deep learning with lagrangian programming neural network (LPNN). First, The LPNN is employed to address the ESP, and its effectiveness is thereafter validated. Subsequently, a deep learning-based LPNN (DLPNN) model accompanied by a specially designed loss function is introduced. This enables the trained DLPNN to solve the ESP in CEMS without the need for repeated steps, which is a limitation of using LPNN alone. Additionally, the dynamic variables in the ESP are incorporated as input variables for training the DLPNN, allowing the model to determine optimal solutions for varying values of these variables. Ultimately, the effectiveness of the introduced approach is confirmed through simulation experiments.

关键词： Deep learning Training Processor scheduling Computational modeling Neural networks Urban areas Programming Dynamic scheduling Dynamic programming Energy management systems

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A Multiband Frequency Reconfigurable Antenna for Wireless Communication

A Multiband Frequency Reconfigurable Antenna for Wireless Co...

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第43届中国控制会议

作者： Rongkai Liang Chuandong Li Youxun Su Weiwei Liang Menggang Chen Zhen Luo College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In order to enhance the adaptability of wireless devices across diverse applications,it becomes imperative for an antenna to embody a multitude of functionalities,including the capacity to dynamically reconfigure the operating frequency,polarization mode,and radiation *** paper introduces a frequency-reconfigurable antenna that incorporates an L-U shaped slot band with a Split-Ring Resonator(SRR).Fabricated on a 1.2 mm low-cost FR4 substrate using a partially grounded design approach,which measures 40 x 35 *** manipulating the bias states of the two PIN diodes,the radiation element current and field distributions can be altered,resulting in reconfigurable bands spanning 2.45 GHz,3.3 GHz,4.5 GHz,7.4GHz,and 9.4 GHz,with an expansive Ultra-Wide Bandwidth(UWB) of 4230 *** antenna design caters to a range of wireless applications,including WLAN(Wireless Local Area Network),WiMAX(Worldwide Interoperability for Microwave Access),Remote Radio,and X-band Satellite *** meticulous simulation optimization,four reconfiguration scenarios are thoroughly examined by presenting and analyzing the simulation results.

关键词： Frequency Bandwidth Reconfigurable Multi-Band Antenna Ultra Wide Band Antenna PIN Diode

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