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arXiv 2025年

作者： Sarvaghad-Moghaddam, Moein Zamani, Morteza Saheb Sedighi, Mehdi Quantum Design Automation Laboratory Department of Computer Engineering Amirkabir University of Technology Tehran Iran

Reversible computation is an emerging technology that has gained significant attention due to its critical role in quantum circuit synthesis and low-power design. This paper introduces a transformation-based method for exact synthesis of reversible circuits. The proposed approach utilizes a modified Quine-McCluskey algorithm to eliminate input-output discrepancies in the truth table, transforming the permutation matrix into an identity matrix. Furthermore, a novel search space reduction technique is presented which, combined with the primary method, enables the synthesis algorithm to handle high-input reversible functions. This approach combines the influence of multiple control qubits on a target qubit, evaluating their collective impact. This aggregation can decrease the control qubit count within quantum gates. Consequently, it proves beneficial for applications like surface code error correction architectures as well as current Noisy Intermediate-Scale Quantum (NISQ) hardwares. Experimental results demonstrate significant improvements over the state-of-the-art exact synthesis methods, achieving up to 99% improvements in terms of the number of levels of T-gates. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 2014-2025页

作者： Xingtang Wu Mingkun Yang Wenbo Lian Min Zhou Hongwei Wang Hairong Dong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China National Research Center of Railway Safety Assessment Beijing Jiaotong UniversityBeijing 100044China

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

关键词： Delay propagation double layer network high speed rail network max-plus algebra

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Fusion enhancement : UAV target detection based on multi-modal GAN 7

Fusion enhancement : UAV target detection based on multi-mod...

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7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Li, Rui Peng, Yi Yang, Qingqing Kunming University of Science and Technology College of Information Engineering and Automation Kunming China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Science Kunming China

ISBN: (纸本)9798350334197

UAV target detection has important application value in the fields of modern military, security and emergency rescue. In order to improve the accuracy and robustness of UAV target detection, this paper uses image fusion technology to enhance the information of input images, and combines YOLOv5 target detection model to introduce attention mechanism for improvement. In the experiment, the generative adversarial network (GAN) is used as the image fusion technology, and the fusion image is generated by changing the structure of the generator and the discriminator. At the same time, the attention mechanism is introduced into the YOLOv5 model to enhance the focus of target detection. The experimental results show that the proposed improved algorithm has achieved significant performance improvement in the UAV target detection task. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Adaptive Tracking Control of an Omnidirectional Mobile Robot System with Uncertainties and Disturbances 49

Adaptive Tracking Control of an Omnidirectional Mobile Robot...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Zhang, Yaozhong Long, Jiang Bai, Zitong Wang, Wei School of Computer Science Northwestern Polytechnical University Xi'an China School of Automation Science and Electrical Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350331820

This paper addresses the tracking problem of an omnidirectional mobile robot (OMR), which is a second-order electromechanical system with unmatched uncertainties and disturbances. The control inputs are the currents of the motors, and the control objective is the tracking control of the real-time position and orientation for the robot. The main features of this paper are summarized as follows. (1) Both the kinematic and the dynamic models for a standard OMR are presented, which explicitly defines the unknown physical parameters of the system as well as the specific mathematical form of disturbances. (2) A new OMR control scheme is proposed based on adaptive back-stepping techniques. It is shown that the OMR can asymptotically track the desired trajectory with any orientation. (3) In addition to numerical simulations, a real OMR experiment platform is established. The effectiveness of the proposed control scheme has been verified with both simulation and experimental results. © 2023 IEEE.

关键词： Mobile robots

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Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems With the Denial-of-Service Attacks and Stochastic Communication Protocol

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 978-989页

作者： Hang Geng Zidong Wang Yun Chen Xiaojian Yi Yuhua Cheng IEEE School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesexUB83PHUnited Kingdom Key Laboratory for IoT and Information Fusion Technology of Zhejiang School of AutomationHangzhou Dianzi UniversityHangzhou 310018China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China

In this paper,a new filtering fusion problem is studied for nonlinear cyber-physical systems under errorvariance constraints and denial-of-service *** prevent data collision and reduce communication cost,the stochastic communication protocol is adopted in the sensor-to-filter channels to regulate the transmission order of *** sensor is allowed to enter the network according to the transmission priority decided by a set of independent and identicallydistributed random *** the defenders’view,the occurrence of the denial-of-service attack is governed by the randomly Bernoulli-distributed *** the local filtering stage,a set of variance-constrained local filters are designed where the upper bounds(on the filtering error covariances)are first acquired and later minimized by appropriately designing filter *** the fusion stage,all local estimates and error covariances are combined to develop a variance-constrained fusion estimator under the federated fusion ***,the performance of the fusion estimator is examined by studying the boundedness of the fused error covariance.A simulation example is finally presented to demonstrate the effectiveness of the proposed fusion estimator.

关键词： Cyber-physical system(CPS) denial-of-service attack stochastic communication protocol(SCP) variance-constrained filtering fusion

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Solar Flare Forecast Model Based on Resampling and Fusion Method

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Research in Astronomy and Astrophysics 2022年第8期22卷 238-248页

作者： Jie Wan Jun-Feng Fu Dai-Min Tan Ke Han Meng-Yao Yu Peng E Laboratory for Space Environment and Physical Sciences Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China School of Computer and Information Engineering Harbin University of CommerceHarbin 150028China

Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and *** such as class imbalance,high time-series sensitivity,and over-localization of important features exist in the sample data used for flare *** design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above *** order to verify the effectiveness of this fusion method,first,we compared the forecast performance of different resampling methods by keeping the forecast model ***,we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models *** use the 2010-2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 *** the conclusion of the above steps,we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare *** addition,after the fusion of one-dimensional convolution and recurrent network with"forget-gate",combined with the SMOTE-ENN to achieve TSS=61%,HSS=61%,TP_(Rate)=77%and TN_(Rate)=83%.This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.

关键词： (Sun:)sunspots Sun:flares Sun:X-rays gamma-rays Sun:magnetic fields Sun:corona

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Adaptive Uniform Performance Control of Strict-Feedback Nonlinear Systems With Time-Varying Control Gain

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 451-461页

作者： Kai Zhao Changyun Wen Yongduan Song Frank L.Lewis IEEE the Department of Electrical and Computer Engineering National University of SingaporeSingapore 119077Singapore the School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore the State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing Key Laboratory of Intelligent Unmanned SystemsSchool of AutomationChongqing UniversityChongqing 400044China the UTA Research Institute University of Texas at ArlingtonFort WorthTX 76118 USA

In this paper,we present a novel adaptive performance control approach for strict-feedback nonparametric systems with unknown time-varying control coefficients,which mainly includes the following ***,by introducing several key transformation functions and selecting the initial value of the time-varying scaling function,the symmetric prescribed performance with global and semi-global properties can be handled uniformly,without the need for control ***,to handle the problem of unknown time-varying control coefficient with an unknown sign,we propose an enhanced Nussbaum function(ENF)bearing some unique properties and characteristics,with which the complex stability analysis based on specific Nussbaum functions as commonly used is no longer ***,by utilizing the core-function information technique,the nonparametric uncertainties in the system are gracefully handled so that no approximator is ***,simulation results verify the effectiveness and benefits of the approach.

关键词： Adaptive control enhanced Nussbaum function(ENF) strict-feedback systems unified prescribed performance

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DocHFormer: Document Image Dewarping via Harmonized Modeling of Hierarchical Priors 27th

DocHFormer: Document Image Dewarping via Harmonized Modelin...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhou, Xinyue Li, Guanting Jiang, Nanfeng Wang, Da-Han Zhang, Xu-Yao Zhu, ShunZhi School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031781186

Document Image Dewarping (DID) task aims to address the issue of geometry distortion and improve image quality. In this paper, we propose a simple but effective method, named DocHFormer, that can take hierarchical priors features of images, including document image mask and coordinate positions, as additional information to realize accurate representation. To better exploit these fused information for dewarping, we take them into a harmonized space random shuffle operation, which can stochastically rearrange the pixels across spatial space and further use inverse operation to recover the original order. This way can adapt to allocate each feature pixel with equal probability and thus make full use of multi-type features. Furthermore, we introduce this mechanism into local self-attention to use linear complexity to input resolution and also design a new feed-forward network with structural modeling to boost representation. With the help of the above components, our proposed DocHFormer can achieve competitive performance with lower complexity and also outperform the existing state-of-the-art on several popular datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image enhancement

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Deep Learning-based Moving Object Segmentation:Recent Progress and Research Prospects

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Machine Intelligence Research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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Document Image Shadow Removal via Frequency Information-Oriented Network 27th

Document Image Shadow Removal via Frequency Information-Ori...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Yang, Fan Zhou, Xinyue Jiang, Nanfeng Wang, Da-Han Zhang, Xu-Yao Li, Guantin Man, Wang Wu, Yun School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031781186

Removing shadows from document images can significantly improve the Quality of Experience (QoE) and boost the performance of the downstream document analysis and recognition tasks. However, existing methods still have limited generalization ability on complex document images and are prone to disrupt the image details. To address this issue, we consider the different shadow types that impact the image content on different frequency sub-bands. This motivates us to exploit frequency-domain information and further design a Frequency Information-oriented Deshadow Network (FID-Net). The proposed FID-Net mainly uses two elaborated modules, named Frequency Feature Extractor (FFE) and a Frequency Feature Refinement (FFR). FFE can generate low/high-frequency features through adaptively decomposing spectra of the shadow image. After that, FFR further refines both frequency features with mutual information operations. With the proposed key designs, extensive experimental results on the commonly used benchmarks demonstrate that the proposed method can learn discriminative shadows and achieve favorable performance against state-of-the-art approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image enhancement

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