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Low-rank subspace representation from optimal coded-aperture for unsupervised classification of hyperspectral imagery

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arXiv 2020年

作者： Zhu, Jianchen Zhang, Tong Zhao, Shengjie Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China School of Software Engineering Tongji University Shanghai201804 China School of Electronic and Information Engineering Tongji University Shanghai201804 China

This paper aims at developing a clustering approach with spectral images directly from the compressive measurements of coded aperture snapshot spectral imager (CASSI). Assuming that compressed measurements often lie approximately in low dimensional subspaces corresponding to multiple classes, state of the art methods generally obtains optimal solution for each step separately but cannot guarantee that it will achieve the globally optimal clustering results. In this paper, a low-rank subspace representation (LRSR) algorithm is proposed to perform clustering on the compressed measurements. In addition, a subspace structured norm is added into the objective of low-rank representation problem exploiting the fact that each point in a union of subspaces can be expressed as a sparse linear combination of all other points and that the matrix of the points within each subspace is low rank. Simulation with real dataset illustrates the accuracy of the proposed spectral image clustering approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Spectroscopy

Design and Implementation of DSP Cache

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Design and Implementation of DSP Cache

International Conference on Communication Technology (ICCT)

作者： Kunkun Liang Jun Wu Haoqi Ren Zhifeng Zhang Bin Tan Electronics and Information Engineering College Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China School of Computer Science Fudan University Shanghai China College of Electronics and Information Engineering Jinggangshan University Ji'an China

ISBN: (纸本)9781665432078

The cache can improve the DSP processor's access speed to external memory and solve the “Storage Wall” problem. Designing an efficient and flexible cache module plays an vital role in improving the memory access efficiency and overall performance of the DSP. Based on the analysis of DSP storage level design requirements, combined with the actual pipeline structure of the DSP processor SWIFT independently developed by our laboratory, in this paper, we design and implement first- level instruction and data cache. For L1 D-Cache, the relevant conflict detection and processing module is designed to support four parallel Load/Store access requests. The size of the cache can be flexibly configured according to actual application requirements to achieve a balance between power consumption and latency. To write back the modified data left in the cache before the cache size is changed, the Cacheclean instruction is designed. Finally, module-level functional verification and logic synthesis are carried out. The results show that the cache function meets expectations, and the critical path after logic synthesis optimization meets the requirement of 1GHz frenuency.

关键词： Frequency synthesizers Power demand Instruction sets Conferences Pipelines Memory management Process control

Maximally permissive control of flexible manufacturing systems with fewest disjunctive constraints

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Maximally permissive control of flexible manufacturing syste...

2012 International Conference onAdvanced Mechatronic systems, ICAMechS 2012

作者： Chen, YuFeng Zhou, MengChu Li, XiaoOu School of Electro-Mechanical Engineering Xidian University Xi'an 710071 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States Departamento de Computación CINVESTAV-IPN Av. IPN 2508 Col. Zacatenco México DF C.P. 07360 Mexico

ISBN: (纸本)9780955529382

For Petri net models whose legal reachability spaces are non-convex, one cannot optimally control them by the conjunctions of linear constraints. This work proposes a method to find a set of linear constraints such that each constraint can forbid all first-met bad markings and every legal marking satisfies at least one constraint. Then, the disjunctions of the obtained constraints can make all legal markings reachable and forbid all first-met bad markings, i.e., the controlled net is live and maximally permissive. The work also develops an integer linear programming model to minimize the number of the constraints. Finally, an example is provided to illustrate the proposed method. © 2012 Intl Jrnal Advanced Mech.

关键词： Flexible manufacturing systems

Epitaxial growth of NaCl on Fe (100) and characterization of Fe/NaCl/Fe magnetic tunnel junctions

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Epitaxial growth of NaCl on Fe (100) and characterization of...

IEEE Conference on Nanotechnology

作者： Yuan-Tao Ji Qiang Li Yong-Chao Tang Lin Li Guo-Xing Miao State Key Laboratory for Manufacturing Systems Engineering and Systems Engineering Institute Xi’an Jiaotong University Xi’an China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (纸本)9781479956234

Growth of NaCl and Fe/NaCl/Fe Magnetic tunneling junctions on Si (100) has been achieved by using a high vacuum electron-beam deposition system. Epitaxial tunnel junctions turn out to be prone to pinholes as well as electrode oxidation. Instead, the best tunneling magnetoresistance we have achieved in this system is on polycrystalline tunnel barriers with thin Mg insertion, and reaching 22.3% at room temperature.

关键词： Iron Junctions Magnetic tunneling Epitaxial growth Tunneling magnetoresistance Electrodes Silicon

LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU

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arXiv 2024年

作者： Zhu, Peng Li, Yuante Hu, Yifan Liu, Qinyuan Cheng, Dawei Liang, Yuqi Department of Computer Science and Technology Tongji University Shanghai China Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Artificial Intelligence Laboratory Shanghai China Seek Data Group Emoney Inc Shanghai China

Stock price prediction is a challenging problem in the field of finance and receives widespread attention. In recent years, with the rapid development of technologies such as deep learning and graph neural networks, more research methods have begun to focus on exploring the interrelationships between stocks. However, existing methods mostly focus on the short-term dynamic relationships of stocks and directly integrating relationship information with temporal information. They often overlook the complex nonlinear dynamic characteristics and potential higher-order interaction relationships among stocks in the stock market. Therefore, we propose a stock price trend prediction model named LSR-IGRU in this paper, which is based on long short-term stock relationships and an improved GRU input. Firstly, we construct a long short-term relationship matrix between stocks, where secondary industry information is employed for the first time to capture long-term relationships of stocks, and overnight price information is utilized to establish short-term relationships. Next, we improve the inputs of the GRU model at each step, enabling the model to more effectively integrate temporal information and long short-term relationship information, thereby significantly improving the accuracy of predicting stock trend changes. Finally, through extensive experiments on multiple datasets from stock markets in China and the United States, we validate the superiority of the proposed LSR-IGRU model over the current state-of-the-art baseline models. We also apply the proposed model to the algorithmic trading system of a financial company, achieving significantly higher cumulative portfolio returns compared to other baseline methods. Our sources are released at https://***/ZP1481616577/Baselines_LSR-IGRU. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph Optimization

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arXiv 2022年

作者： Tian, Xuebo Zhao, Junqiao Ye, Chen Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China

Ego-pose estimation and dynamic object tracking are two key issues in an autonomous driving system. Two assumptions are often made for them, i.e. the static world assumption of simultaneous localization and mapping (SLAM) and the exact ego-pose assumption of object tracking, respectively. However, these assumptions are difficult to hold in highly dynamic road scenarios where SLAM and object tracking become correlated and mutually beneficial. In this paper, DL-SLOT, a dynamic Lidar SLAM and object tracking method is proposed. This method integrates the state estimations of both the ego vehicle and the static and dynamic objects in the environment into a unified optimization framework, to realize SLAM and object tracking (SLOT) simultaneously. Firstly, we implement object detection to remove all the points that belong to potential dynamic objects. Then, LiDAR odometry is conducted using the filtered point cloud. At the same time, detected objects are associated with the history object trajectories based on the time-series information in a sliding window. The states of the static and dynamic objects and ego vehicle in the sliding window are integrated into a unified local optimization framework. We perform SLAM and object tracking simultaneously in this framework, which significantly improves the robustness and accuracy of SLAM in highly dynamic road scenarios and the accuracy of objects' states estimation. Experiments on public datasets have shown that our method achieves better accuracy than A-LOAM. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

A Relational Taxonomy of services for Large Scale service Repositories

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A Relational Taxonomy of Services for Large Scale Service Re...

IEEE International Conference on Web services (ICWS)

作者： Yan Wu Chungang Yan Zhijun Ding Pengwei Wang Changjun Jiang Mengchu Zhou Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China School of Electronics and Information Engineering Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

With the rapid development of service-oriented computing (SOC) and service-oriented architecture (SOA), the number of services is rapidly increasing. How to organize and manage services effectively in repositories to improve the efficiency of service discovery and composition is important. This paper proposes three categorization rules to classify services for a large scale repository to form a relational taxonomy. The service retrieve scope can be drastically narrowed by this taxonomy. Therefore, the efficiency of service discovery and service composition can be greatly improved. We evaluate and compare the performance of the proposed method and other related ones via a publicly available test set, ICEBE05. The experimental results validate the effectiveness and high efficiency of the proposed one.

关键词： Taxonomy Web services Educational institutions system-on-a-chip Quality of service Conferences Computers

DL-SLOT: Dynamic LiDAR SLAM and object tracking based on collaborative graph optimization

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arXiv 2022年

作者： Tian, Xuebo Zhu, Zhongyang Zhao, Junqiao Tian, Gengxuan Ye, Chen Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China

Ego-pose estimation and dynamic object tracking are two critical problems for autonomous driving systems. The solutions to these problems are generally based on their respective assumptions, i.e., the static world assumption for simultaneous localization and mapping (SLAM) and the accurate ego-pose assumption for object tracking. However, these assumptions are challenging to hold in dynamic road scenarios, where SLAM and object tracking become closely correlated. Therefore, we propose DL-SLOT, a dynamic LiDAR SLAM and object tracking method, to simultaneously address these two coupled problems. This method integrates the state estimations of both the autonomous vehicle and the stationary and dynamic objects in the environment into a unified optimization framework. First, we used object detection to identify all points belonging to potentially dynamic objects. Subsequently, a LiDAR odometry was conducted using the filtered point cloud. Simultaneously, we proposed a sliding window-based object association method that accurately associates objects according to the historical trajectories of tracked objects. The ego-states and those of the stationary and dynamic objects are integrated into the sliding window-based collaborative graph optimization. The stationary objects are subsequently restored from the potentially dynamic object set. Finally, a global pose-graph is implemented to eliminate the accumulated error. Experiments on KITTI datasets demonstrate that our method achieves better accuracy than SLAM and object tracking baseline methods. This confirms that solving SLAM and object tracking simultaneously is mutually advantageous, dramatically improving the robustness and accuracy of SLAM and object tracking in dynamic road scenarios. Copyright © 2022, The Authors. All rights reserved.

关键词： Optical radar

Polynomial-time hierarchy of computable reals

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Journal of Computational Information systems 2011年第4期7卷 1108-1115页

作者： Chen, Qingliang Su, Kaile Wu, Lijun Department of Computer Science Jinan University Guangzhou 510632 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of High Confidence Software Technologies Ministry of Education Peking University Beijing China Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia School of Computer Science and Engineering University of Electronic Science and Technology Chengdu 610054 China

In mathematics, various representations of real numbers have been investigated and all these representations are proved to be mathematically equivalent. Furthermore, it is known that all effective versions of these representations lead to the same class of "computable real numbers". However, when subrecursive (such as primitive recursive) is taken into account, these representations can lead to different notions of "computable real numbers". This paper will look into the polynomial-time version of the problem for computable real numbers under different representations. We will summarize the known results to exhibit the comprehensive hierarchy they form. Our goal is to clarify systematically how the polynomial-time computability depends on the representations of the real numbers. Copyright © 2011 Binary Information Press.

关键词： Polynomial approximation