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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 136-146页

作者： Wang, Xin Zhou, Yuhao Luo, Biao Jiang, Yuming Huang, Tingwen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China School of Automation Central South University Changsha410083 China Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim7491 Norway T&M University at Qatar Doha23874 Qatar

This article is concerned with the event-triggered adaptive finite-time control problem for a class of switched cyber-physical systems (CPSs) subject to uncertain deception attacks. We deploy the finite time command filter to alleviate the possible explosion of complexity rendered by the virtual control signal’s duplicative differentiation. To stabilize the target system with a guaranteed disturbance rejection performance index, a disturbance observer is constructed by using fuzzy logic systems (FLS) with the hope of estimating the unknown external disturbance. Furthermore, the Nussbaum gain is utilized to resist the unknown control efficiency generated by uncertain deception attacks. Based on the common Lyapunov function (CLF) method, sufficient conditions are derived to ensure that all signals in the closed-loop system are uniformly bounded at a finite time. Finally, the simulation example shows the validity and efficacy of the developed control method. © 2023 Institute of Electrical and Electronics Engineers. All rights reserved.

关键词： Closed loop systems

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Face recognition from near-infrared images with convolutional neural network

Face recognition from near-infrared images with convolutiona...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Xiaotong Zhang Min Peng Tong Chen Chonqging Key Laboratory of Non-linear Circuit and Intelligent Information Processing Southwest University China

ISBN: (纸本)9781509028610

Owing to the vigorous development of face recognition, near-infrared (NIR) face recognition technology with light insensitivity has attracted increasing attention. However, the traditional methods for NIR face recognition feature the hand-crafted feature design. In this paper, we present a convolutional neural network (CNN) for NIR face recognition. CNN is a multiplayer feed-forward neural network which can automatically learn the features from the raw images and provide partial invariance to illumination, scale and deformation. Experimental results on PolyU-NIRFD database show that our proposed CNN architecture has higher recognition rate compared with the traditional recognition methods, such as Gabor-directional binary code (GDBC), Zernike moments and Hermite kernels (ZMHK).

关键词： Face recognition Feature extraction Neural networks Lighting Face Convolutional codes Databases

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Kernel least mean square algorithm with mixed kernel

Kernel least mean square algorithm with mixed kernel

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Qitang Sun Lujuan Dang Wanli Wang Shiyuan Wang College of Electronic and Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

This paper presents a novel kernel least square algorithm with mixed kernel (KLMS-MK) to improve the filtering performance of kernel least mean square (KLMS). By applying the convex combination method to the kernel function in KLMS, KLMS-MK bears the advantages of both the Gaussian kernel and the Laplace kernel. In KLMS-MK, the mixed parameter for the convex combination is updated with the stochastic gradient descent. Therefore, the steady-state mean square error (MSE) and the convergence rate are improved by KLMS-MK, simultaneously. Simulation results on chaotic time series prediction and nonlinear regression validate the excellent performance of KLMS-MK from the aspects of the convergence rate and estimation accuracy.

关键词： Kernel Testing Signal processing algorithms Gaussian noise Convergence Approximation algorithms Time series analysis

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A Fusion Shallow and Deep Features Network for Facial StO2 Stress Classification

A Fusion Shallow and Deep Features Network for Facial StO2 S...

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IEEE information Technology, Networking, Electronic and Automation Control Conference

作者： Haolin Xia Sirui Sun Xinyu Liu Ju Zhou Hanpu Wang Tong Chen School of Electronic and Information Engineering Southwest University Chongqing China Key Laboratory of Non-Linear Circuit and Intelligent Information Processing of Chongqing Chongqing China Institute of Legal Psychology and Intelligent Computing Chongqing China

Stress is an emotional state that affects our lives, so it is vital to detect it accurately. Numerous studies have shown that tissue oxygen saturation (StO2) is an effective physiological signal for identifying different stress states. However, previous StO2 feature extraction methods relied too heavily on baselines to be realized in practice. In this paper, a two-stream network combining shallow and deep features, called CRNet, is proposed for baseline-independent StO2 stress classification. In CRNet, shallow features are extracted using a CNN network and deep features are extracted using a ResNet network. For the extracted high-dimensional deep features, MLP module is employed for dimensionality reduction, which can effectively combine the two levels of features and improve the feature extraction capability of the network. Experimental results show that CRNet can significantly improve the performance of StO2 stress classification to the state-of-the-art (SOTA) even when using only raw imbalanced data.

关键词： Dimensionality reduction Automation Anxiety disorders Feature extraction Physiology Stress

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Exploring Regulation Effect of Jogging on Human Emotion Based on Pulse Signal

Exploring Regulation Effect of Jogging on Human Emotion Base...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Jianguang Yuan Guangyuan Liu Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

ISBN: (纸本)9781509035595

Until recently, claims for the psychological benefits of physical exercise have tended to precede supportive evidence. Actually, emotional effects of exercise remain confusing, both positive and negative effects being reported. Meanwhile, several studies have shown that the aerobic exercise has impact on human's mood through making subjective evaluation of the Profile of Mood States (POMS) before and after exercise. However, the conclusion via comparing with the Profile of Mood States (POMS) scores was lack of the objective basis. In order to explain the result that exercise has effects of adjustment to fear emotion from the objective point of view, therefore, this study researched exercise which can improve mood based on the subjects' physiological signal, and analyzed data using the affective computing. Issues involved in this study are discussed.

关键词： Mood Physiology Time series analysis Affective computing Fatigue Computational intelligence nonlinear circuits

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Facial StO2: A New Promising Biometric Identity

Facial StO2: A New Promising Biometric Identity

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

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.

关键词： Databases Face recognition Biological system modeling Aging Security Bioinformatics Stress

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Long Video Micro-expression Spotting Based On OCC Theory

Long Video Micro-expression Spotting Based On OCC Theory

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： BingTong Liu ZheYuan Zhang Ju Zhou HanPu Wang Tong Chen Institute of Legal Psychology and Intelligent Computing Southwest University Chongqing China Chongqing Key Laboratory of Non-Linear Circuit and Intelligent Information Processing Chongqing China School of Electronic and Information Engineering Southwest University Chongqing China

The generation of micro-expression (ME) is unconscious and unaffected by human subjective consciousness. It can reveal hidden emotions in humans, which has important applications in the domains of psychological diagnosis, lie detection, and so on. ME detection, which aims to locate ME apex frames in long videos, is the foundation of ME recognition. In this paper, we propose a ME detection method based on One-Class Classification (OCC) theory for long videos. The method is the first to use neutral expression frames to detect MEs, which addresses the problem of insufficient training samples in ME detection. We design a geometric motion feature based on the prior knowledge from the FACS and utilize it in conjunction with the features extracted by CNN to train separate one-class classifiers for ME detection. Finally, we evaluate the proposed method on publicly available datasets CASME I, CASME II, SAMM, and a mixed database comprising data from the three datasets, to verify the feasibility of the proposed method in both single-database and cross-database ME detection. The experimental results show that our method outperforms three other ME detection methods, demonstrating its ability to more accurately locate ME apex frames in long videos.

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Accelerated Distributed Optimization over Directed Graphs with Row and Column-Stochastic Matrices

Accelerated Distributed Optimization over Directed Graphs wi...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Jinhui Hu Yifan Zhu Huaqing Li Zheng Wang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

In this paper, we study distributed optimization problem over multi-agent networks where the goal is to find the global optimal of a sum of convex functions over strongly connected and directed graphs. A novel distributed algorithm is proposed where both row and column-stochastic matrices are utilized to bypass the limits of the implementation of doubly-stochastic matrices or eigenvector estimation in related work. Besides, it has an evident expression and accelerated convergence by introducing the momentum term. Combining the Generalized Small Gain Theorem with linear Time Invariant (LTI) system inequality, the algorithm is proved to be able to linearly converge to the exact optimal solution. Furthermore, the ranges of stepsize and momentum paramater are characterized, respectively. Finally, simulation results illustrate effectiveness of the method and correctness of theoretical analysis.

关键词： Radio frequency Convergence Optimization Acceleration Eigenvalues and eigenfunctions Convex functions linear matrix inequalities

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An ECG Monitoring System Based on Android

An ECG Monitoring System Based on Android

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International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Ruiqi Zhang Zhengchun Hua Chen Chen Guangyuan Liu Wanhui Wen School of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (数字)9781728165172

ISBN: (纸本)9781728165189

This study aims to design a real-time electrocardiogram (ECG) and heart rate monitoring system based on Android. The system connects Android device and a Shimmer3 ECG module, which is a wearable ECG device collecting ECG data with five electrodes. The ECG signal is amplified and filtered by internal circuit processing in Shimmer3 ECG module, and the ECG data is transmitted to an Android phone via Bluetooth. The baseline drift in ECG signal is removed through wavelet decomposition and reconstruction. Then, the processed ECG data are used to find the R wave peaks by an algorithm for automatic R peak locating and RR interval calculation. RR interval waveform is plotted and displayed on an Android phone in real time. Finally, ECG and RR intervals are saved for data playback and subsequent analysis.

关键词： Electrocardiography Bluetooth Real-time systems Smart phones Monitoring Heart rate

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A Distributed Dynamic Resource Allocation Strategy in A Large-scale Micro-grids Group

A Distributed Dynamic Resource Allocation Strategy in A Larg...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Zao Fu Xing He Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

In this paper, a dynamic economic dispatch problem (DEDP) with renewable energy generators is studied. With the purpose of minimizing the cost of DEDP and optimally allocate the load demand among the interconnected generators considering ramp-rate limits and generation limits, an effective continuous-time distributed algorithm based on interior point methods and primal-dual methods is proposed. In order to overcome the drawbacks of the renewable energy, a parallel system composed with flywheel energy storage systems and renewable energy generators is proposed to work in a constant power output mode. In addition, the using of switched systems makes the optimal solution more accurate. The excellent performance of the proposed algorithm is verified by IEEE 30-bus system with the REG based simulation.

关键词： Dynamic economic dispatch renewable energy Continuous-time distributed algorithm Renewable energy flywheel energy storage system MICRO-GRID dynamos rate limitation Switched systems DYNAMIC ECONOMIC ANALYSIS Resource utilization management of resources

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