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Fast least-squares prestack time migration via accelerating the explicit calculation of Hessian matrix with dip-angle Fresnel zone

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Petroleum science 2022年第3期19卷 1031-1047页

作者： Bo-Wu Jiang Jiang-Jie Zhang Hao Zhang Wen-Kai Lu College of Mechanical and Electrical Engineering Beijing University of Chemical TechnologyBeijing100029China The Institute for Artificial Intelligence(THUAI) Beijing100084China State Key Laboratory of Intelligent Technology and Systems Beijing100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing100084China The Department of Automation Tsinghua UniversityBeijing100084China Key Laboratory of Petroleum Resource Research Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China Institute of Geomechanics Chinese Academy of Geological SciencesBeijing100081China

Amplitude versus offset analysis is a fundamental tool for determining the physical properties of reservoirs but generally hampered by the blurred common image gathers(CIGs).The blurring can be optimally corrected using the blockwise least-squares prestack time migration(BLS-PSTM),where common-offset migrated sections are divided into a series of blocks related to the explicit offsetdependent Hessian matrix and the following inverse filtering is iteratively applied to invert the corresponding ***,calculating the Hessian matrix is *** present a fast BLS-PSTM via accelerating Hessian calculation with dip-angle Fresnel zone(DFZ).DFZ is closely related to optimal migration aperture,which significantly attenuates migration swings and reduces the computational cost of ***,our fast BLS-PSTM is implemented as a two-stage ***,we limit the aperture for any imaging point with an approximated the projected Fresnel zone before calculating the Hessian ***,we determine whether a seismic trace contributes to the imaging point via DFZ during calculating the Hessian *** tests on synthetic and field data validate the distinct speedup with higher-quality CIGs compared to BLS-PSTM.

关键词： Prestack time migration Fresnel zone Hessian Least squares migration Migrated gather

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Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation

arXiv

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arXiv 2024年

作者： Han, Yu Long, Ziwei Zhang, Yanting Wu, Jin Fang, Zhijun Fan, Rui The School of Computer Science and Technology Donghua University Shanghai201620 China The Department of Electronics and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong SAR Hong Kong Hong Kong Group The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

Correspondence matching plays a crucial role in numerous robotics applications. In comparison to conventional hand-crafted methods and recent data-driven approaches, there is significant interest in plug-and-play algorithms that make full use of pre-trained backbone networks for multi-scale feature extraction and leverage hierarchical refinement strategies to generate matched correspondences. The primary focus of this paper is to address the limitations of deep feature matching (DFM), a state-of-the-art (SoTA) plug-and-play correspondence matching approach. First, we eliminate the pre-defined threshold employed in the hierarchical refinement process of DFM by leveraging a more flexible nearest neighbor search strategy, thereby preventing the exclusion of repetitive yet valid matches during the early stages. Our second technical contribution is the integration of a patch descriptor, which extends the applicability of DFM to accommodate a wide range of backbone networks pre-trained across diverse computer vision tasks, including image classification, semantic segmentation, and stereo matching. Taking into account the practical applicability of our method in real-world robotics applications, we also propose a novel patch descriptor distillation strategy to further reduce the computational complexity of correspondence matching. Extensive experiments conducted on three public datasets demonstrate the superior performance of our proposed method. Specifically, it achieves an overall performance in terms of mean matching accuracy of 0.68, 0.92, and 0.95 with respect to the tolerances of 1, 3, and 5 pixels, respectively, on the HPatches dataset, outperforming all other SoTA algorithms. Our source code, demo video, and supplement are publicly available at ***/GCM. © 2024, CC BY.

关键词： Semantics

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Van der Waals ferroelectric transistors:the all-round artificial synapses for high-precision neuromorphic computing

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Chip 2023年第2期2卷 8-15页

作者： Zhongwang Wang Xuefan Zhou Xiaochi Liu Aocheng Qiu Caifang Gao Yahua Yuan Yumei Jing Dou Zhang Wenwu Li Hang Luo Junhao Chu Jian Sun School of Physics and Electronics Central South UniversityChangsha 410083China State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of OptoelectronicsDepartment of Materials ScienceFudan UniversityShanghai 200433China National Key Laboratory of Integrated Circuit Chips and Systems Zhang Jiang Fudan International Innovation CenterFudan UniversityShanghai 200433China Raith China Beijing 100013China

state number,operation power,dynamic range and conductance weight update linearity are key synaptic device performance metrics for high-accuracy and low-power-consumption neuromorphic com-puting in ***,high linearity and low power consump-tion couldn’t be simultaneously achieved by most of the reported synaptic devices,which limits the performance of the *** work demonstrates van der Waals(vdW)stacked ferroelectric field-effect transistors(FeFET)with single-crystalline ferroelectric *** are of fine vdW interface and partial polar-ization switching of multi-domains under electric field pulses,which makes the FeFETs exhibit multi-state memory characteristics and ex-cellent synaptic *** also exhibit a desired linear conduc-tance weight update with 128 conductance states,a sufficiently high dynamic range of G_(max)/G_(min)>120,and a low power consumption of 10 fJ/spike using identical *** on such an all-round device,a two-layer artificial neural network was built to conduct Modified Na-tional Institute of Standards and technology(MNIST)digital num-bers and electrocardiogram(ECG)pattern-recognition simulations,with the high accuracies reaching 97.6%and 92.4%,*** remarkable performance demonstrates that vdW-FeFET is of obvious advantages in high-precision neuromorphic computing applications.

关键词： Ferroelectric transistors Ferroelectric van der Waals het-erostructures Artificial synapses Neuromorphic computing

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Quantum Remote state Preparation Based on Quantum Network Coding

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computers, Materials & Continua 2022年第10期73卷 119-132页

作者： Zhen-Zhen Li Zi-Chen Li Yi-Ru Sun Haseeb Ahmad Gang Xu Xiu-Bo Chen School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Information Security Center State key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan School of Information Science and Technology North China University of TechnologyBeijing100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province China

As an innovative theory and technology,quantum network coding has become the research hotspot in quantum network *** this paper,a quantum remote state preparation scheme based on quantum network coding is *** with the general quantum remote state preparation schemes,our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network,by designing the appropriate encoding and decoding steps for quantum network *** is worth mentioning,from the network model,this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly ***,it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding,and it also makes the proposed scheme more applicable to the large-scale quantum *** addition,the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum ***,the security of the proposed scheme is ***,this scheme can always achieve the success probability of 1 and 1-max flow of value ***,the communication efficiency of the proposed scheme is ***,the proposed scheme turns out to be practicable,secure and efficient,which helps to effectively enrich the theory of quantum remote state preparation.

关键词： Quantum remote state preparation quantum network coding quantum k-pair network

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Evolutionary Dynamic Optimization-Based Calibration Framework for Agent-Based Financial Market Simulators

Evolutionary Dynamic Optimization-Based Calibration Framewor...

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Congress on Evolutionary Computation

作者： Zhenhua Yang Muyao Zhong Peng Yang Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Department of Statistics and Data Science Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

The agent-based financial market simulators serve as an important validation tool for trading strategies. For high-fidelity simulation, it is pivotal to calibrate the parameters of a simulator so that the generated simulation data resembles the observed real market data of interest. In traditional calibration methods, it is typical that the parameters of the simulator are set to be time-invariant. However, the dynamic nature of the real financial market introduces various variability into the behaviors of the market participants over different time intervals, posing in-herent limitations to the traditional methods. A more reasonable approach might involve employing a simulator with time-variant parameters. This suggests that the model parameters can be dynamically adjusted at different stages of the simulation to adapt to the evolving market. Consequently, the calibration problem of the financial market simulators can be treated as a dynamic optimization problem. To dynamically calibrate the simulators, we introduce an Evolutionary Dynamic Optimization (EDO) framework. By monitoring the changes of the best fitness, the whole simulation time interval is adaptively divided into multiple stages. Then the Negatively Correlated Search (NCS) algorithm is employed to effectively adjust the parameters at different simulation stages to better simulate the real financial market. Empirical results on both synthetic and real data verify that our dynamic calibration framework significantly outperforms traditional calibration methods that fixing a parameter for the whole simulation interval. The proposed strategy of detecting dynamic changes is also shown to be more reliable than the naive method of manually segmenting stages. In terms of calibration time, our proposed method significantly improves by nearly 93% compared to the fixed parameter setting, and approximately 61% compared to manual segmentation calibration.

关键词： Adaptation models Fluctuations Heuristic algorithms Computational modeling Scalability Manuals Data models

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Seismic impedance inversion based on cycle-consistent generative adversarial network

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Petroleum science 2022年第1期19卷 147-161页

作者： Yu-Qing Wang Qi Wang Wen-Kai Lu Qiang Ge Xin-Fei Yan The Institute for Artificial Intelligence Tsinghua University(THUAI)Beijing100084China State Key Laboratory of Intelligent Technology and Systems Tsinghua UniversityBeijing100084China Beijing National Research Center for Information Science and Technology(BNRist) Tsinghua UniversityBeijing100084China The Department of Automation Tsinghua UniversityBeijing100084China The Research Institute of Petroleum Exploration and Development China National Petroleum Corporation(CNPC)Beijing100083China

Deep learning has achieved great success in a variety of research fields and industrial ***,when applied to seismic inversion,the shortage of labeled data severely influences the performance of deep learning-based *** order to tackle this problem,we propose a novel seismic impedance inversion method based on a cycle-consistent generative adversarial network(Cycle-GAN).The proposed Cycle-GAN model includes two generative subnets and two discriminative *** kinds of loss,including cycle-consistent loss,adversarial loss,and estimation loss,are adopted to guide the training *** from the proposed structure,the information contained in unlabeled data can be extracted,and adversarial learning further guarantees that the prediction results share similar distributions with the real ***,a neural network visualization method is adopted to show that the proposed CNN model can learn more distinguishable features than the conventional CNN *** robustness experiments on synthetic data sets show that the proposed method can achieve better performances than other methods in most *** the blind-well experiments on real seismic profiles show that the predicted impedance curve of the proposed method maintains a better correlation with the true impedance curve.

关键词： Seismic inversion Cycle GAN Deep learning Semi-supervised learning Neural network visualization

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

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26th International Conference on Industrial technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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Performance Analysis of Distributed Filtering under Mismatched Noise Covariances

arXiv

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arXiv 2024年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems, namely the standard performance evaluation index, the nominal performance evaluation index, and the estimation error covariance. We derive difference expressions among these indices and establish one-step relations among them under various mismatched noise covariance scenarios. We particularly reveal the effect of the consensus fusion on these relations. Furthermore, the recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these indices under the collective observability condition, and show this convergence condition of the nominal performance evaluation index can guarantee the convergence of the estimation error covariance. Additionally, we prove that the estimation error covariance of the consensus-based distributed filter under mismatched noise covariances can be bounded by the Frobenius norms of the noise covariance deviations and the trace of the nominal performance evaluation index. Finally, the effectiveness of the theoretical results is verified by numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Wiener filtering

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An Isomerism Learning Model to Solve Time-Varying Problems Through intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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Computation of an Emptiable Minimal Siphon in a Subclass of Petri Nets Using Mixed-Integer Programming

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 219-226页

作者： Shouguang Wang Wenli Duo Xin Guo Xiaoning Jiang Dan You Kamel Barkaoui MengChu Zhou the School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China the Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China the Department of Computer Science Conservatoire National des Arts et MétiersParis 75141France the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems Macao University of Science and TechnologyMacao 999078China

Deadlock resolution strategies based on siphon control are widely *** computational efficiency largely depends on siphon ***-integer programming(MIP)can be utilized for the computation of an emptiable siphon in a Petri net(PN).Based on it,deadlock resolution strategies can be designed without requiring complete siphon enumeration that has exponential *** to this reason,various MIP methods are proposed for various subclasses of *** work proposes an innovative MIP method to compute an emptiable minimal siphon(EMS)for a subclass of PNs named S^(4)*** particular,many particular structural characteristics of EMS in S4 PR are formalized as constraints,which greatly reduces the solution *** results show that the proposed MIP method has higher computational ***,the proposed method allows one to determine the liveness of an ordinary S^(4)PR.

关键词： Automated manufacturing systems deadlocks discrete event system mixed-integer programming(MIP) Petri nets(PN) siphons

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