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arXiv 2023年

作者： Xu, Tao Xi, Wang He, Jianping Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

This paper exploits the weak approximation method to study a zero-sum linear differential game under mixed strategies. The stochastic nature of mixed strategies poses challenges in evaluating the game value and deriving the optimal strategies. To overcome these challenges, we first define the mixed strategy based on time discretization given the control period δ. Then, we design a stochastic differential equation (SDE) to approximate the discretized game dynamic with a small approximation error of scale O(δ2) in the weak sense. Moreover, we prove that the game payoff is also approximated in the same order of accuracy. Next, we solve the optimal mixed strategies and game values for the linear quadratic differential games. The effect of the control period is explicitly analyzed when the payoff is a terminal cost. Our results provide the first implementable form of the optimal mixed strategies for a zero-sum linear differential game. Finally, we provide numerical examples to illustrate and elaborate on our results. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions:progress in efficacy and geographic equality

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National Science Review 2024年第2期11卷 103-113页

作者： Tao Xue Ruohan Wang Meng Wang Yanying Wang Dan Tong Xia Meng Conghong Huang Siqi Ai Fangzhou Li Jingyuan Cao Mingkun Tong Xueqiu Ni Hengyi Liu Jianyu Deng Hong Lu Wei Wan Jicheng Gong Shiqiu Zhang Tong Zhu Institute of Reproductive and Child Health National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics Ministry of Education Key Laboratory of Epidemiology of Major Diseases(PKU) School of Public Health Peking University Health Science Centre State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health Peking University Advanced Institute of Information Technology Peking University Department of Epidemiology and Environmental Health School of Public Health and Health ProfessionsUniversity at Buffalo State Key Joint Laboratory of Environment Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking University Department of Earth System Science Tsinghua University School of Public Health Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of HealthFudan University College of Land Management Nanjing Agricultural University National&Local Joint Engineering Research Center for Rural Land Resources Use and Consolidation Clean Air Asia

Clean air actions （CAAs） in China have been linked to considerable benefits in public ***,whether the beneficial effects of CAAs are equally distributed geographically is *** high-resolution maps of the distributions of major air pollutants (fine particulate matter[PM2.5]and ozone[O3]) and population,we aimed to track spatiotemporal changes in health impacts from,and geographic inequality embedded in,the reduced exposures to PM2.5and O3from 2013 to *** used a method established by the Global Burden of Diseases *** analyzing the changes in loss of life expectancy（LLE） attributable to PM2.5and O3,we calculated the gain of life expectancy （GLE） to quantify the health benefits of the air-quality ***,we assessed the geographic inequality embedded in the GLE using the Gini index （GI）.Based on risk assessments of PM2.5and O3,during the first stage of CAAs（2013 to 2017）,the mean GLE was 1.87 *** of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed （GI 0.44）.During the second stage of CAAs（2017 to 2020）,the mean GLE increased to 3.94 months and geographic inequality decreased （GI 0.18）.According to our assessments,CAAs were enhanced,from the first to second stages,in terms of not only preventing premature mortality but also ameliorating health *** enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5and *** findings will contribute to optimizing future CAAs.

关键词： clean air action public health inequality fine particulate matter ozone

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Research on Robust Measurement Method of Heart Rate Using Remote Photoplethysmography Based on Adversarial Learning Network with High and Low Frequency Features

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IEEE Transactions on Circuits and systems for Video Technology 2025年第6期35卷 5208-5222页

作者： Zhai, Dezhao Chen, Wei Ding, Yinghao Yu, Ming Li, Qinwei Wu, Hang Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China People's Liberation Army Systems Engineering Institute Academy of Military Sciences Tianjin300161 China Civil Aviation University of China Tianjin Key Laboratory for Advanced Signal Processing Tianjin300300 China Nankai University School of Artificial Intelligence Tianjin300381 China

Remote Photoplethysmography (rPPG) is a non-contact method for measuring heart rate (HR) through facial video, breaking the constraints of contact measurements and offering broad application prospects. However, in real monitoring scenarios, the distance of subjects and facial illumination often vary. This leads to degradation of rPPG signals due to changes in facial resolution and light intensity. This paper presents the High and Low Frequency Feature Adversarial Learning Network (HLFF-AL), which utilizes feature space interpolation and composite feature capture to perform multi-band global and local signal extraction. By adopting an adversarial learning strategy, it enhances the capability to capture semantic information of rPPG under varying resolutions and lighting, bridging the differences in rPPG signal generation due to resolution changes. While maintaining accuracy in HR measuring, the robustness of the network is improved to achieve robust measurement of HR via rPPG. Even under high-resolution conditions, the Mean Absolute Error (MAE) for the three public datasets - unchanging lighting (COHFACE, UBFC-rPPG) and varying lighting (BUAA-MIHR) - reached 1.10 bpm, 1.64 bpm, and 4.41 bpm, respectively, with a mere 0.29 bpm difference in MAE between high and low resolutions on the BUAA-MIHR dataset. This demonstrates that HLFF-AL can predict more robust rPPG signals in various resolutions and lighting scenarios, achieving competitive results compared to state-of-the-art methods. © 1991-2012 IEEE.

关键词： Heart

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Reinforcement Learning with Hierarchical Graph Structure for Flexible Job Shop Scheduling

Reinforcement Learning with Hierarchical Graph Structure for...

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Complex systems and Intelligent Science (CSIS-IAC), International Annual Conference on

作者： Linli Zhang Dewei Li dept. of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

The flexible job shop scheduling problem (FJSP) is a NP-hard combinatorial optimization challenge, having extensive real-world industrial applications. For a given instance of FJSP, a scheduling solution need to be devised, which entails determining the appropriate machine for each operation and establishing the sequence in which operations are processed on a given machine, all while adhering to certain constraints. However, many of the methods are lacking in flexibility, unable to cope effectively with multi-relational operations and machine selection scenarios. This can make the representation of state and action challenging in practice, leading to a significant increase in decision complexity. This paper considers these issues by a hierarchical graph structure with a model that synergistically integrates two modules: the environment and the decision module. The environment module is characterized by a hierarchical graph neural network which defines the multi-relational FJSP instance where all machine and operation data are stored. The decision module incorporates the Actor-Critic networks, designed to train reasoning strategies and enhance decision performance, based on the states and rewards provided at each step by the environment module. The objective is to derive optimal scheduling strategies through interactions between the decision agent and the environment, targeting the minimum resources consumed or makespan. Numerical simulations validate the efficacy of the proposed approach, showing its potential to yield superior results and thereby enhance performance.

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Robust Probabilistic Prediction for Stochastic Dynamical systems

arXiv

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arXiv 2023年

作者： Xu, Tao He, Jianping The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

It is critical and challenging to design robust predictors for stochastic dynamical systems (SDSs) with uncertainty quantification (UQ) in the prediction. Specifically, robustness guarantees the worst-case performance when the predictor’s information set of the system is inadequate, and UQ characterizes how confident the predictor is about the predictions. However, it is difficult for traditional robust predictors to provide robust UQ because they were designed to robustify the performance of point predictions. In this paper, we investigate how to robustify the probabilistic prediction for SDS, which can inherently provide robust distributional UQ. To characterize the performance of probabilistic predictors, we generalize the concept of likelihood function to likelihood functional, and prove that this metric is a proper scoring rule. Based on this metric, we propose a framework to quantify when the predictor is robust and analyze how the information set affects the robustness. Our framework makes it possible to design robust probabilistic predictors by solving functional optimization problems concerning different information sets. In particular, we design a class of moment-based optimal robust probabilistic predictors and provide a practical Kalman-filter-based algorithm for implementation. Extensive numerical simulations are provided to elaborate on our results. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Solo Adaptation for Distributed Synchronization With Application to Event-Triggered Linear Multi-Agent systems

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IEEE Transactions on Automatic control 2025年第6期70卷 4225-4232页

作者： Chen, Ci Zheng, Zhiyang Lewis, Frank L. Xie, Kan Xie, Shengli Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education School of Automation Guangzhou510006 China Guangdong University of Technology School of Automation Guangdong Guangzhou510006 China The University of Texas at Arlington UTA Research Institute Fort Worth76118 United States Guangdong University of Technology 111 Center for Intelligent Batch Manufacturing Based on IoT Technology School of Automation Guangzhou China Guangdong University of Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of Education School of Automation Guangzhou510006 China

We study a solo adaptation-based protocol design problem for distributed synchronization of event-triggered linear multi-agent systems (MAS) over general directed graphs. We show that a solo adaptive gain, a locally static control gain matrix, and a distributed state measurement are sufficient for obtaining adaptive distributed synchronization of linear MAS over directed graphs without any prior knowledge of the global communication network. We then extend the solo adaptation structure to formulate an event-triggered synchronization control protocol. The main feature of our result is that the time for triggering a subsequent event is now computed using the distributed event-triggered state measurement, rather than the continuous-time state measurement. © 1963-2012 IEEE.

关键词： Continuous time systems

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A data-assisted adaptive detection algorithm for shortwave burst signals 5

A data-assisted adaptive detection algorithm for shortwave b...

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5th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2022

作者： Yi Wei, Feng Wen Zhong, Qu Yan, Zhao Yu Mei, Zhou Pla Strategic Support Force Information Engineering University College of Information System Engineering Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (数字)9781665484749

ISBN: (纸本)9781665484749

For shortwave signals with unique code frame structure, a data-assisted adaptive burst detection algorithm is proposed in this paper. The algorithm weakens the high bottom-noise undulation of signal correlation values due to shortwave channel fading by using a locally normalized sliding differential correlation. Also based on this, an adaptive gate limit detection strategy based on sliding window comparison judgments is used to improve the burst detection accuracy. This paper focuses on the effects of signal-to-noise ratio and shortwave channel environment on the performance of this algorithm, and simulation experiments are conducted under different conditions. The simulation results show that the algorithm has good robustness and can still achieve good detection results in the case of low signal-to-noise ratio as well as short-wave poor channels. © 2022 IEEE.

关键词： Fading channels

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Joint Optimization of Privacy Protection and Resource Allocation for Vehicular Edge Networks

Joint Optimization of Privacy Protection and Resource Alloca...

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IEEE International Conference on Communications in China (ICCC)

作者： Tianqi Gao Hongfeng Tao Yuanzhi Ni Jun Shi Fengcheng Jiang School of Internet of Things Engineering Jiangnan University Wuxi China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

In the last decade, the service of vehicular networks has benefited from the rapid development of advanced communication and computing technologies including edge computing. For vehicular network operators, it is valuable to study how to realize the accurate allocation of edge computing resource on the premise of protecting users’ privacy. In this paper, we design a histogram publishing algorithm based on differential privacy. The algorithm first classifies tasks according to the characteristics of computing requests, then interferes categorized tasks and designs a shuffling algorithm based on Blum Blum Shub (BBS). Finally, the frequency histogram of computing resource is obtained by post-processing of the Expectation-Maximum (EM) algorithm. The simulation results verify the accuracy and superiority of the proposed histogram publishing algorithm by comparing it with the existing methods.

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Observation-based Optimal control Law Learning with LQR Reconstruction

arXiv

引用

arXiv 2023年

作者： Qu, Chendi He, Jianping Duan, Xiaoming Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

Designing controllers to generate various trajectories has been studied for years, while recently, recovering an optimal controller from trajectories receives increasing attention. In this paper, we reveal that the inherent linear quadratic regulator (LQR) problem of a moving agent can be reconstructed based on its trajectory observations only, which enables one to learn the optimal control law of the agent autonomously. Specifically, the reconstruction of the optimization problem requires estimation of three unknown parameters including the target state, weighting matrices in the objective function and the control horizon. Our algorithm considers two types of objective function settings and identifies the weighting matrices with proposed novel inverse optimal control methods, providing the well-posedness and identifiability proof. We obtain the optimal estimate of the control horizon using binary search and finally reconstruct the LQR problem with above estimates. The strength of learning control law with optimization problem recovery lies in less computation consumption and strong generalization ability. We apply our algorithm to the future control input prediction and the discrepancy loss is further derived. Numerical simulations and hardware experiments on a self-designed robot platform illustrate the effectiveness of our work. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

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control Input Inference of Mobile Agents under Unknown Objective

arXiv

引用

arXiv 2023年

作者： Qu, Chendi He, Jianping Duan, Xiaoming Wu, Shukun The Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

Trajectory and control secrecy is an important issue in robotics security. This paper proposes a novel algorithm for the control input inference of a mobile agent without knowing its control objective. Specifically, the algorithm first estimates the target state by applying external perturbations. Then we identify the objective function based on the inverse optimal control, providing the well-posedness proof and the identifiability analysis. Next, we obtain the optimal estimate of the control horizon using binary search. Finally, the agent's control optimization problem is reconstructed and solved to predict its input. Simulation illustrates the efficiency and the performance of the algorithm. Copyright © 2023, The Authors. All rights reserved.

关键词： Mobile agents

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