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arXiv 2024年

作者： Li, Huaqing Ran, Liang Zheng, Lifeng Li, Zhe Hu, Jinhui Li, Jun Huang, Tingwen The Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China The Department of Automation Central South University Changsha410083 China The Department of Biomedical Engineering City University of Hong Kong Hong Kong Texas A & M University at Qatar Doha23874 Qatar

This paper considers a class of noncooperative games in which the feasible decision sets of all players are coupled together by a coupled inequality constraint. Adopting the variational inequality formulation of the game, we first introduce a new local edge-based equilibrium condition and develop a distributed primal-dual proximal algorithm with full information. Considering challenges when communication delays occur, we devise an asynchronous distributed algorithm to seek a generalized Nash equilibrium. This asynchronous scheme arbitrarily activates one player to start new computations independently at different iteration instants, which means that the picked player can use the involved out-dated information from itself and its neighbors to perform new updates. A distinctive attribute is that the proposed algorithms enable the derivation of new distributed forward-backward-like extensions. In theoretical aspect, we provide explicit conditions on algorithm parameters, for instance, the step-sizes to establish a sublinear convergence rate for the proposed synchronous algorithm. Moreover, the asynchronous algorithm guarantees almost sure convergence in expectation under the same step-size conditions and some standard assumptions. An interesting observation is that our analysis approach improves the convergence rate of prior synchronous distributed forward-backward-based algorithms. Finally, the viability and performance of the proposed algorithms are demonstrated by numerical studies on the networked Cournot competition. Copyright © 2024, The Authors. All rights reserved.

关键词： Iterative methods

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Prox-DBRO-VR: A Unified Analysis on Decentralized Byzantine-Resilient Composite Stochastic Optimization with Variance Reduction and non-Asymptotic Convergence Rates

arXiv

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arXiv 2023年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Guo, Xiaoyu Ran, Liang Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Science Program Texas A&M University at Qatar Doha23874 Qatar

Decentralized stochastic gradient algorithms resolve efficiently large-scale finite-sum optimization problems when all agents in the network are reliable. However, most of these algorithms are not resilient to adverse conditions, such as malfunctioning agents, software bugs, and cyber attacks. This paper aims to handle a class of general composite finite-sum optimization problems over multi-agent systems (MASs) in the presence of an unknown number of Byzantine agents. Based on the proximal mapping method, variance-reduced (VR) techniques, and a norm-penalized approximation strategy, we propose a decentralized Byzantine-resilient and proximal-gradient algorithmic framework, dubbed Prox-DBRO-VR, which achieves an optimization and control goal using only local computations and communications. To remove asymptotically the variance generated by evaluating the local noisy stochastic gradients, we incorporate two localized VR techniques (SAGA and LSVRG) into Prox-DBRO-VR to design Prox-DBRO-SAGA and ProxDBRO-LSVRG. By analyzing the contraction relationships among the gradient-learning error, resilient consensus condition, and convergence error in a unified theoretical framework, it is demonstrated that both Prox-DBRO-SAGA and Prox-DBRO-LSVRG, with a well-designed constant (resp., decaying) step-size, converge linearly (resp., sub-linearly) inside an error ball around the optimal solution to the original problem under standard assumptions. A trade-off between the convergence accuracy and Byzantine resilience in both linear and sub-linear cases is also characterized. In numerical experiments, the effectiveness and practicability of the proposed algorithms are manifested via resolving a decentralized sparse machine-learning problem over MASs under various Byzantine attacks. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Effects of Negative Stimulation After Exercise on Frontal Asymmetry in Unregular Exercisers

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IOP Conference Series: Materials Science and Engineering 2019年第5期612卷

作者： Tengfei Wang Guangyuan Liu School of Electronic and Information Engineering Southwest University Chongqing 400700 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing 400700 China

As a signal to recognize emotion, the electroencephalogram (EEG) is used widely. Frontal asymmetry is not only related to emotion, but also affected by exercise. The purpose of our research is to explore the effects of exercise for negative emotion, and how the activity of the frontal of the college students who did not exercise regularly is. We used the frontal asymmetry between F3 and F4 channels of the alpha band. The result showed that the power of frontal asymmetry increased after exercise compared to that before exercise within 3 seconds after stimulation, and the change of the power during the 2nd second was more obvious. The activity of the frontal of the students without exercise habits can be altered by exercise. The frontal asymmetry is related to emotion, which confirms that exercise has an effect on the students without exercise habits after negative stimulation.

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Decentralized nonconvex Robust Optimization over Unsafe Multiagent Systems: System Modeling, Utility, Resilience, and Privacy Analysis

arXiv

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arXiv 2024年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Cheng, Huqiang Guo, Xiaoyu Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Key Laboratory of Dependable Services Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing400044 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multiagent systems (MASs). Considering an unsafe MAS with these two issues, this paper targets the resolution of a class of nonconvex optimization problems under the Polyak-Lojasiewicz (P-L) condition. To address this problem, we first identify and construct the unsafe MAS model. Under this kind of unfavorable MASs, we mask the local gradients with Gaussian noises and adopt a resilient aggregation method self-centered clipping (SCC) to design a differentially private (DP) decentralized Byzantine-resilient algorithm, namely DP-SCC-PL, which simultaneously achieves differential privacy and Byzantine resilience. The convergence analysis of DP-SCC-PL is challenging since the convergence error can be contributed jointly by privacy-preserving and Byzantine-resilient mechanisms, as well as the nonconvex relaxation, which is addressed via seeking the contraction relationships among the disagreement measure of reliable agents before and after SCC aggregation, together with the optimal gap. Theoretical results reveal that DP-SCC-PL achieves consensus among all reliable agents and sublinear (inexact) convergence with well-designed step-sizes. It has also been proved that if there are no privacy issues and Byzantine agents, then the asymptotic exact convergence can be recovered. Numerical experiments verify the utility, resilience, and differential privacy of DP-SCC-PL by tackling a nonconvex optimization problem satisfying the P-L condition under various Byzantine attacks. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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𝒮-asymptotically 𝓌-periodic mild solutions for noninstantaneous impulsive integro-differential equations with state-dependent delay

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Mathematical Methods in the Applied Sciences 2023年第9期46卷

作者： Yinuo Wang Chuandong Li Hao Deng Hongjuan Wu Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing 400715 China Communicated by: J. Banasiak

A kind of nonlinear noninstantaneous impulsive equation with state-dependent delay is studied here. By utilizing suitable fixed point theorem and the theory of semigroup in Banach space, the uniqueness and existence results of S $$ \mathcal{S} $$ -asymptotically w $$ w $$ -periodic mild solutions are obtained, respectively. In the end, two examples are presented to demonstrate the validity of the obtained results.

关键词： fixed point theorem integro-differential equations noninstantaneous impulse S$$ \mathcal{S} $$-asymptotically w$$ w $$-periodic mild solution state-dependent delay

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Effects of Acute Moderate Intensity Exercise on the EEGFrontal Alpha Asymmetry

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Journal of Physics: Conference Series 2020年第7期1486卷

作者： Zhangyan Xiao Zhengji Long Pengfei Gao Chaoling Qin Guangyuan Liu 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.

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Octopus-Inspired Multichannel Tactile Sensor for Enhanced Underwater Material Identification

SSRN

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SSRN 2024年

作者： Hao, Yutao Sun, Yanshuo Wen, Jing Gao, Xiaobo Wang, Yutong Zhu, Zhiyuan Wang, Zhong Lin Chen, Baodong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing101400 China School of Nanoscience and Engineering University of Chinese Academy of Sciences Beijing100049 China Research Institute of Technology of Shougang Group Beijing100043 China The Key Laboratory of High Temperature Electromagnetic Materials and Structure of MOE Wuhan University of Science and Technology Wuhan430081 China Georgia Institute of Technology AtlantaGA30332-0245 United States

The sustainable development of the ocean requires sensors capable of detecting objects in underwater or high humidity conditions. However, traditional sensors struggle in complex underwater environments due to signal attenuation, biofouling, and flow interference, which seriously affect the performance and reliability. Inspired by the tactile system of octopus suckers, we developed a tactile sensor that mimics the structure of octopus tentacle suckers, ingeniously harnessing triboelectric tactile receptors (TTRs) to emulate the mechanism of cephalopod-specific chemoreceptors (CRs), aiming to address the challenging problem of underwater object recognition. Additionally, the superhydrophobic treatment increases the microstructure of the sensor surface, effectively mitigating environmental interference and improved underwater performance, resulting in a 67% increase in voltage output, a sensitivity of 0.195 V kPa-1, and a remarkable response time of only 85 ms. Most importantly, we have constructed an underwater material identification system (UMIS) to achieve 98% accuracy by integrating machine learning, which enables precise identification and quantitative sensing of underwater objects, offering novel insights and directions for the intelligence and autonomy of underwater robots. © 2024, The Authors. All rights reserved.

关键词： Shellfish

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Comparative Analysis of Personality Recognition in Response to Virtual Reality and Two-Dimensional Emotional Stimulus Using ECG Signals

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ACM Transactions on Interactive intelligent Systems 1000年

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

Personality primarily refers to the unique and stable way of a person’s thinking and behavior. A few studies have recently been conducted on personality recognition using physiological signals, most of which have used two-dimensional (2D) emotional stimulus materials. Virtual reality (VR) has been utilized in many fields, and its superiority over 2D in emotion recognition has been proven. However, relevant research on VR scenes is lacking in the field of personality recognition. In this study, based on the psychological principle that emotional arousal can expose an individual’s personality, we attempt to explore the feasibility and effect of using electrocardiogram (ECG) signals in response to VR emotional stimuli for personality identification. For this purpose, a VR-2D emotion-induction experiment was conducted in which ECG signals were collected, and physiological datasets of emotional personalities were constructed through preprocessing and feature extraction. Statistical analysis of the emotion scale scores and ECG features of the participants showed that the VR group had a higher number of significantly correlated features. Meanwhile, VR- and 2D-based personality recognition models were constructed using machine learning algorithms. The results showed that the VR-based personality recognition model achieved better results for the four personality dimensions, with a maximum accuracy of 79.76%. These findings indicate that VR not only enhances the physiological correlation between emotion and personality but also improves the classification accuracy of personality recognition.

关键词： Big Five personality Electrocardiogram Emotion Personality recognition Virtual reality

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TSW-FD: A Novel Temporal and Spatial Domain Weight Analysis of Feature Difference for Micro-Expression Spotting

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Zhihao Zhang Fan Mo Ke Zhao Tong Chen Xiaolan Fu State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences Beijing 100101 China Department of Psychology University of Chinese Academy of Sciences Beijing 100049 China Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Southwest University Chongqing 400715 China Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology Chongqing 400715 China

The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from the original feature difference (FD) analysis, in this paper, we proposed a novel temporal and spatial domain weight analysis of feature difference (TSW-FD) to achieve micro-expression spotting. The experimental results showed that TSW-FD improved 17.86% and 24.21% in F1-Score comparing to the FD in CASME II and SMIC-E-HS.

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An Image Denoising Method Based on Deep Residual GAN

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Journal of Physics: Conference Series 2020年第3期1550卷

作者： Ziyuan Wang Lidan Wang Shukai Duan Yunfei Li Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing 400715 China Schoolof Electronic and information engineering Southwest University Chongqing400715 China College of Artificiall Intelligence Southwest University Chongqing 400715 China Braininspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China

As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most of them is lack of capability when customers want more perceptual details of the image without information loss. In this paper, a deep residual network based on generative adversarial (GAN) network was proposed to complete the image denoising mission. Firstly, a generative-adversarial network structure based on residual blocks was designed. Secondly, a refined loss function was given to train the GAN network. The well designed loss function can help the generated image to be very close to the clear counterpart (ground truth) while enhancing more details in colours and brightness. Finally, extensive experiments show that our network is not only convincing for images denoising, but also effective for other image process tasks, such as image defogging, medical CT denoising etc., presenting impressive and competitive effects.

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