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arXiv 2025年

作者： Cui, Bohan Yu, Xinyi Giua, Alessandro Yin, Xiang Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical and Electronic Engineering University of Cagliari Cagliari09123 Italy

In this paper, we investigate the control synthesis problem for Signal Temporal Logic (STL) specifications in the presence of uncontrollable agents. Existing works mainly address this problem in a robust control setting by assuming the uncontrollable agents are adversarial and accounting for the worst-case scenario. While this approach ensures safety, it can be overly conservative in scenarios where uncontrollable agents have their own objectives that are not entirely opposed to the system’s goals. Motivated by this limitation, we propose a new framework for STL control synthesis within the Stackelberg game setting. Specifically, we assume that the system controller, acting as the leader, first commits to a plan, after which the uncontrollable agents, acting as followers, take a best response based on the committed plan and their own objectives. Our goal is to synthesize a control sequence for the leader such that, for any rational followers producing a best response, the leader’s STL task is guaranteed to be satisfied. We present an effective solution to this problem by transforming it into a single-stage optimization problem and leveraging counterexample guided synthesis techniques. We demonstrate that the proposed approach is sound and identify conditions under which it is optimal. Simulation results are also provided to illustrate the effectiveness of the proposed framework. © 2025, CC BY.

关键词： control system synthesis

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Immune particle swarm optimization of linear frequency modulation in acoustic communication

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Journal of systems Engineering and Electronics 2015年第3期26卷 450-456页

作者： Haipeng Ren Yang Zhao Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

With the exploration of the ocean, underwater acoustic communication has attracted more and more attention in recent years. The underwater acoustic channel is considered to be one of the most complicated channels because it suffers from more serious multipath effect, fewer available bandwidths and quite complex noise. Since the signals experience a serious distortion after being transmitted through the underwater acoustic channel, the underwater acoustic communication experiences a high bit error rate （BER）. To solve this problem, carrier waveform inter- displacement （CWlD） modulation is proposed. It has been proved that CWlD modulation is an effective method to decrease BER. The linear frequency modulation （LFM） carrier-waves are used in CWlD modulation. The performance of the communication using CWID modulation is sensitive to the change of the frequency band of LFM carrier-waves. The immune particle swarm optimization （IPSO） is introduced to search for the optimal frequency band of the LFM carrier-waves, due to its excellent performance in solving complicated optimization problems. The multi-objective and multi- peak optimization nature of the IPSO gives a suitable description of the relationship between the upper band and the lower band of the LFM carrier-waves. Simulations verify the improved perfor- mance and effectiveness of the optimization method.

关键词： underwater acoustic communication carrier waveform inter-displacement （CWlD） multi-objective optimization immune particle swarm optimization （IPSO）.

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Pathological axonal enlargement in connection with amyloidosis,lysosome destabilization,and bleeding is a major defect in Alzheimer’s disease

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Neural Regeneration Research 2026年第2期21卷 790-799页

作者： Hualin Fu Jilong Li Chunlei Zhang Guo Gao Qiqi Ge Xinping Guan Daxiang Cui Institute of Nano Biomedicine and Engineering School of Sensing Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghaiChina National Center for Translational Medicine Shanghai Jiao Tong UniversityShanghaiChina Department of Automation Shanghai Jiao Tong UniversityShanghaiChina The Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina

Alzheimer’s disease is a multi-amyloidosis disease characterized by amyloid-βdeposits in brain blood vessels,microaneurysms,and senile *** amyloid-βdeposition affects axon pathology has not been examined *** used immunohistochemistry and immunofluorescence staining to analyze the forebrain tissue slices of Alzheimer’s disease *** axonal amyloidosis with distinctive axonal enlargement was observed in patients with Alzheimer’s *** average,amyloid-β-positive axon diameters in Alzheimer’s disease brains were 1.72 times those of control brain ***,axonal amyloidosis was associated with microtubule-associated protein 2 reduction,tau phosphorylation,lysosome destabilization,and several blood-related markers,such as apolipoprotein E,alpha-hemoglobin,glycosylated hemoglobin type A1C,and *** destabilization in Alzheimer’s disease was also clearly identified in the neuronal soma,where it was associated with the co-expression of amyloid-β,Cathepsin D,alpha-hemoglobin,actin alpha 2,and collagen type *** suggests that exogenous hemorrhagic protein intake influences neural lysosome ***,the data showed that amyloid-β-containing lysosomes were 2.23 times larger than control ***,under rare conditions,axonal breakages were observed,which likely resulted in Wallerian *** summary,axonal enlargement associated with amyloidosis,micro-bleeding,and lysosome destabilization is a major defect in patients with Alzheimer’s *** finding suggests that,in addition to the well-documented neural soma and synaptic damage,axonal damage is a key component of neuronal defects in Alzheimer’s disease.

关键词： Alzheimer’s disease amyloid-β amyloidosis axonal enlargement hemoglobin hemorrhage lysosome destabilization neuropil thread tau Wallerian degeneration

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Air Pollution Monitoring By Integrating Local and Global information in Self-Adaptive Multiscale Transform Domain

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IEEE Transactions on Multimedia 2025年

作者： Gu, Ke Liu, Yuchen Liu, Hongyan Liu, Bo Qiao, Junfei Lin, Weisi Zhang, Wenjun Beijing University of Technology School of Information Science and Technology Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Massey University School of Mathematical and Computational Sciences New Zealand Nanyang Technological University College of Computing and Data Science Singapore Shanghai Jiao Tong University Institute of Image Communication and Information Processing Shanghai China

As the deadliest form of pollution, air pollution had a prolonged severe damage to the human health and life safety of nearly 99% of the world's population. Facing to the problem that billions of tons of pollutants discharged into the air per year by industrial activities, this paper proposed a novel image-based air pollution monitor (IAPM) by incorporating local and global information in the self-adaptive multiscale transform domain, so as to achieve the timely and effective leakage detection of typical air pollutants from a single image. To be specific, this paper first developed a screen-shaped module according to two significant findings in visual neuroscience, which include the high sensitivity of human eyes to horizontal and vertical stimuli and the center-surround inhibition, by designing and fusing the square module, horizontal strip module and vertical strip module parallelly for simulating the behaviour of human eyes to extract local features. Second, the learnable weights and proportional mapping were applied to incorporate the screen-shaped module and lightweight vision transformer as backbone, towards more richly exploiting and fusing local and global information just as the way a brain perceives external stimuli. Third, a new self-adaptive multiscale transform domain method was devised based on two motivations from the visual characteristics of multiscale perception and the brain characteristics of self-adaptive domain transform to modify the backbone by using the operations of pooling and pointwise convolution. Extensive experiments implemented on the datasets of carbon particulate matters and ethylene leakage confirmed the superior monitoring performance of the proposed IAPM model beyond the state-of-the-art (SOTA) peers by an accuracy gain of about 4%. Furthermore, the proposed IAPM model only required 0.089 GFLOPs and 0.15 million model parameters, remarkably outperforming SOTA competitors in computational efficiency and storage resources. © 1999-2

关键词： information leakage

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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

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IEEE Transactions on Consumer Electronics 2025年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Xue, Xingsi Zhang, Fuquan Fuzhou University College of Computer and Big Data Fuzhou China Polytechnic University of Catalonia Department of Automatic Control Barcelona Spain Putian University New Engineering Industry College Putian China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Minjiang University College of Computer and Control Engineering Fuzhou China Sichuan Conservatory of Music Digital Media Art Key Laboratory of Sichuan Province Chengdu China Minjiang University Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Fuzhou China Fuzhou China

Driver drowsiness electroencephalogram (EEG) signal monitoring can promptly alert drivers of their drowsiness in edge-end Consumer Electronics (CE), thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end Lightweight Dual Graph Convolutional Network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. To further enhance the application of CE, we apply Adaptive Pruning Optimization (APO) to the channels and neurons of LDGCN, which nearly halves the inference latency. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization, outperforming existing state-of-the-art algorithms. © 1975-2011 IEEE.

关键词： Neurons

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SN-LiDAR: Semantic Neural Fields for Novel Space-time View LiDAR Synthesis

arXiv

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arXiv 2025年

作者： Chen, Yi Deng, Tianchen Zhao, Wentao Wang, Xiaoning Xi, Wenqian Chen, Weidong Wang, Jingchuan Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200030 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200030 China Ruijin Hospital Shanghai Jiao Tong University School of Medicine China Renji hospital Shanghai Jiao Tong University School of Medicine China

Recent research has begun exploring novel view synthesis (NVS) for LiDAR point clouds, aiming to generate realistic LiDAR scans from unseen viewpoints. However, most existing approaches do not reconstruct semantic labels, which are crucial for many downstream applications such as autonomous driving and robotic perception. Unlike images, which benefit from powerful segmentation models, LiDAR point clouds lack such large-scale pre-trained models, making semantic annotation time-consuming and labor-intensive. To address this challenge, we propose SN-LiDAR, a method that jointly performs accurate semantic segmentation, high-quality geometric reconstruction, and realistic LiDAR synthesis. Specifically, we employ a coarse-to-fine planar-grid feature representation to extract global features from multi-frame point clouds and leverage a CNN-based encoder to extract local semantic features from the current frame point cloud. Extensive experiments on SemanticKITTI and KITTI-360 demonstrate the superiority of SN-LiDAR in both semantic and geometric reconstruction, effectively handling dynamic objects and large-scale scenes. Codes will be available on https://***/dtc111111/SN-Lidar. © 2025, CC BY-NC-SA.

关键词： Semantic Segmentation

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Data-Driven Distributionally Robust Mixed-Integer control through Lifted control Policy

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IEEE Transactions on Automatic control 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. ©1963-2012 IEEE.

关键词： Mixed-integer linear programming

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Connectivity-maintaining Consensus of Multi-agent systems With Communication Management Based on Predictive control Strategy

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 700-710页

作者： Jie Wang Shaoyuan Li Yuanyuan Zou Key Laboratory of System Control and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China IEEE

This paper studies the connectivity-maintaining consensus of multi-agent *** the impact of the sensing ranges of agents for connectivity and communication energy consumption,a novel communication management strategy is proposed for multi-agent systems so that the connectivity of the system can be maintained and the communication energy can be *** this paper,communication management means a strategy about how the sensing ranges of agents are adjusted in the process of reaching *** proposed communication management in this paper is not coupled with controller but only imposes a constraint for controller,so there is more freedom to develop an appropriate control strategy for achieving *** the multi-agent systems with this novel communication management,a predictive control based strategy is developed for achieving *** results indicate the effectiveness and advantages of our scheme.

关键词： Consensus energy-saving multi-agent system predictive control

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Symplectic Wigner Distribution in the Linear Canonical Transform Domain: Theory and Application

arXiv

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arXiv 2025年

作者： He, Yangfan Zhang, Zhichao School of Communication and Artificial Intelligence School of Integrated Circuits Nanjing Institute of Technology Nanjing211167 China School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science Application of Hainan Province Hainan Normal University Haikou571158 China Key Laboratory of Numerical Simulation of Sichuan Provincial Universities School of Mathematics and Information Sciences Neijiang Normal University Neijiang641000 China

This paper devotes to combine the chirp basis function transformation and symplectic coordinates transformation to yield a novel Wigner distribution (WD) associated with the linear canonical transform (LCT), named as the symplectic WD in the LCT domain (SWDL). It incorporates the merits of the symplectic WD (SWD) and the WD in the LCT domain (WDL), achieving stronger capability in the linear frequency-modulated (LFM) signal frequency rate feature extraction while maintaining the same level of computational complexity. Some essential properties of the SWDL are derived, including marginal distributions, energy conservations, unique reconstruction, Moyal formula, complex conjugate symmetry, time reversal symmetry, scaling property, time translation property, frequency modulation property, and time translation and frequency modulation property. Heisenberg’s uncertainty principles of the SWDL are formulated, giving rise to three kinds of lower bounds attainable respectively by Gaussian enveloped complex exponential signal, Gaussian signal and Gaussian enveloped chirp signal. The optimal symplectic matrices corresponding to the highest time-frequency resolution are generated by solving the lower bound optimization (minimization) problem. The time-frequency resolution of the SWDL is compared with those of the SWD and WDL to demonstrate its superiority in LFM signals time-frequency energy concentration. A synthesis example is also carried out to verify the feasibility and reliability of the theoretical analysis. Copyright © 2025, The Authors. All rights reserved.

关键词： Wigner-Ville distribution

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PERFORMANCE LIMITATIONS FOR A CLASS OF KLEINMAN control systemS

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Journal of systems Science & Complexity 2014年第3期27卷 445-452页

作者： CAI Xin LI Shaoyuan Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System.Control and Information ProcessingMinistry of Education

This paper provides preliminary results on performance limitations for a class of discrete time Kleinman control systems whose open loop poles lie strictly outside the unit circle. By exploiting the properties of the Kleinman controllers and using of Mgebraic Riccati equation （ARE）, the relationship between total control energy of Kleinman control systems and the minimum energy needed to stabilize the open-loop systems is revealed. The result reflects how the horizon length of Kleinman controllers affects the performance of the closed-loop systems and quantifies how close the performance of Kleinman control systems is to the minimum energy.

关键词： Algebraic Riccati equation Kleinman control minimum energy control performance limitations zero terminal receding horizon control.

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