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检索条件"机构=Science and Technology on Complex System Control"

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An Adversarial Defense Algorithm Based on Triplet Network and Voting Decision

An Adversarial Defense Algorithm Based on Triplet Network an...

引用

2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Zheng, Haonan Zhao, Jiajia Tan, Wei School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In the field of artificial intelligence, neural network is one of the key technologies used for image classification and recognition. However, recent work has demonstrated that deep neural networks are easily attacked by adversarial examples to make misjudgments. Adversarial examples are almost indistin-guishable from normal examples and yet cannot be classified correctly by neural networks. The existence of adversarial examples is a major obstacle to the practical application and deployment of neural networks, so the research on adversarial defense algorithms is an important topic in the field of AI security. This paper proposes an adversarial example defense algorithm based on a triplet network and voting decision mechanism. Firstly, two neural networks with different structures are trained based on normal dataset. Secondly, the first network is fine-tuned using the adversarial examples generated by these two networks, resulting in a third neural network. Then, these three neural networks are used as sub-networks in parallel to construct a triplet network. Through adversarial training and differences in structures, the transferability of adversarial examples among the three sub-networks is weakened. Finally, the final classification result is obtained by majority voting, based on the parallel output results of the three sub-networks. Through the complementarity between these three sub-networks, the defense against adversarial examples is realized. The experimental results demonstrate the effectiveness of this algorithm. © 2022 IEEE.

关键词： Deep neural networks

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A Provably Stable SBP-SAT FDTD Subgridding Method without Modifying Yee's Grids

A Provably Stable SBP-SAT FDTD Subgridding Method without Mo...

引用

2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Wang, Yuhui Diao, Guijie Ni, Hong Yang, Shunchuan Research Institute for Frontier Science Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781665442282

A stable finite-difference time-domain (FDTD) sub-grid ding method using the summation-by-parts simultaneous approximation term (SBP-SAT) technique is proposed. To meet the SBP properties and keep Yee's grids unchanged, the projection operators are carefully designed to extrapolate fields on the boundaries. Then, the SATs are used to weakly enforce the boundary conditions between multiple mesh blocks with different mesh sizes. Therefore, its long-term stability is theoretically guaranteed. An iris filter is simulated to validate the effectiveness of the proposed method. Results show that the proposed SBP-SAT FDTD subgridding method is stable, accurate and efficient. © 2023 IEEE.

关键词： Finite difference time domain method

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A Stable and Symmetric FDTD Subgridding Method with Arbitrary Grid Ratio

A Stable and Symmetric FDTD Subgridding Method with Arbitrar...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Deng, Langran Gong, Ningbo Diao, Guijie Yang, Shunchuan Research Institute for Frontier Science Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781665442282

A stable and symmetric finite-difference time-domain (FDTD) subgridding method is proposed to effectively and accurately solve the three-dimensional electromagnetic prob-lems. The linear interpolation coefficient (LIC) and the length cutoff coefficient (LCC) are carefully designed to guarantee the stability of the proposed method. In addition, the proposed method is applicable to arbitrary grid ratios and nested meshes. A practical multiscale example is used to validate its accuracy and efficiency. © 2023 IEEE.

关键词： Finite difference time domain method

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Optimal Terrain Following Trajectory Regeneration Using Linear Gauss Pseudo-Spectral Method

Optimal Terrain Following Trajectory Regeneration Using Line...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Feng, Yijun Chen, Wanchun Yang, Liang Wei, Donghui Beihang University School of Astronautics Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

A numerical method for two-dimensional terrain following optimal trajectory regeneration is proposed in this paper, which corrects the planned optimal trajectory to avoid collision with previously unknown obstacles. The neighboring extremal problem is established near the optimal terrain following trajectory, which can be regarded as a two-point boundary-value problem (TPBVP) and solved using Linear Gauss Pseudo-Spectral (LGP) method. Compared with the classical backward sweep method for solving TPBVPs, LGP method is much faster in obtaining approximate results. Numerical simulations are provided to validate the effectiveness and demonstrate the features of the problem. © 2019 IEEE.

关键词： Numerical methods

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Channel Estimation Based on Lorentzian Adaptive Algorithm in a-stable Noise Environment 9

Channel Estimation Based on Lorentzian Adaptive Algorithm in...

引用

9th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2020

作者： Cherednichenko, Aleksey Huang, Xinqi Wang, Yanyan Li, Yingsong Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9781728198057

This paper presented a p-norm constraint Lorentzian adaptive algorithm to estimate the sparse multi-path channel ina-stable noise environment. We derived the proposed algorithm based on the Lagrange multiplier method and we also evaluated the performance of the developed adaptive algorithm via estimating a sparse multi-path channel. The gotten results on the basis of computer simulations proved that the developed Lorentzian adaptive algorithm is superior to the popular method in the comparisons. © 2020 IEEE.

关键词： Channel estimation

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Observer-based fault detection for affine nonlinear systems with disturbances and uncertainties 35

Observer-based fault detection for affine nonlinear systems ...

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第35届中国控制会议

作者： HAN Huayun YANG Ying LI Linlin Chen Yu State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University School of Automation and Electrical Engineering University of Science and Technology Beijing the Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Beijing Institute of Astronautics System Engineering

ISBN: (纸本)9781509009107

This paper is concerned with the integrated design schemes of L observer-based fault detection（FD） systems for affine nonlinear processes with disturbances and uncertainties,*** this end,a so called L observer-based FD scheme is studied ***,the integrated design approaches for nonlinear systems with disturbances and uncertainties are addressed,*** the end,examples are given to illustrate the effectiveness of the proposed approaches.

关键词： Robust Fault Detection Observer Design Affine Nonlinear systems

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A Comparative Study on Adversarial Attacks for Visible and Infrared Images

A Comparative Study on Adversarial Attacks for Visible and I...

引用

2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Guo, Haiwang Tan, Wei Zhao, Jiajia School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Agent Cooperation Laboratory Science and Technology on Complex System Control and Intelligent Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In recent years, the booming development of artificial intelligence has driven the development and progress of society. With its excellent performance, deep learning has been widely used in many fields, including some security-sensitive fields such as unmanned systems, auto-driving and so on. Research has found that deep neural networks are vulnerable to adversarial samples, which can lead to misclassification of neural networks and can cause serious safety incidents. Hence, the study of adversarial samples has received increasing attention, and researchers have conducted studies from different perspectives, and relevant research results have emerged. However, most of these studies have focused on visible images, and few have studied infrared images, which play an important role in military and other important fields. In this paper, a comparative study on adversarial attacks for visible and infrared images is presented. A number of adversarial attack experiments are conducted on ResNet18 and VGG16 models for visible and infrared images. By comparing the experimental results, the characteristics of infrared adversarial samples are derived relative to those with visible adversarial samples. Then, a gradient attack method from a frequency domain perspective is proposed. The adversarial perturbation noise is added to the low frequency component of images. It is verified experimentally that the proposed method improves the transferability of infrared adversarial samples compared to some baseline methods. © 2022 IEEE.

关键词： Deep neural networks

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Distributed Finite-Time Cooperative Guidance Against a Moving Target: A Finite-Time Observer Approach

Distributed Finite-Time Cooperative Guidance Against a Movin...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Xiaofei, Dong Zhang, Ren School of Automation Science and Electrical Engineering Beihang University Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9780738146577

This paper investigates the cooperative guidance issue for multiple unmanned aerial vehicles (UAVs) for simultaneous attacks on maneuvering targets with a prescribed angle formation. Each UAV is accessible to the relative information with respect to the target while the absolute information of the target is unavailable. Also, each UAV just interacts with its neighbors locally. By introducing the integral sliding mode technique, a finite-time observer for the exact estimation of the absolute information of the target is designed. With the help of such an observer, a distributed cooperative guidance algorithm is developed such that both the time-to-go estimate consensus and angle formation objectives are achieved in finite time given that the undirected graph is connected. Finally, a simulation example is presented to validate the efficiency of the suggested guidance algorithm. © 2021 IEEE.

关键词： Antennas

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Monocular visual based obstacle distance estimation method for ultra-low altitude flight

Monocular visual based obstacle distance estimation method f...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Cheng, Jin Wei, Donghui Chen, Wanchun Gao, Wang Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Astronautics Beijing China

ISBN: (纸本)9781728137926

This paper focuses on the problem of ultra-low-altitude flight obstacle distance estimation for monocular vision-assisted aircraft. First, the basic error model of distance estimation using sequence images is derived and the phenomenon of "epipole dead zone" is revealed. Then the distance estimation algorithm based on pairs of coplanar points is proposed as well as its error model. This algorithm is proved to be a solution of the "epipole dead zone" problem theoretically. Finally, numerical simulations show that the proposed distance estimation algorithm can effectively improve the accuracy of distance estimation in the "epipole dead zone". © 2019 IEEE.

关键词： Vision

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Improved RRT Autonomous Exploration Method Based on Hybrid Clustering Algorithm

Improved RRT Autonomous Exploration Method Based on Hybrid C...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yin, Yizhen Ma, Hongjun Liang, Xinkai College of Information Science and Engineering Northeastern University Liaoning Shenyang China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

In autonomous robot exploration, it is very important that the robot can autonomously plan the exploration path of the unknown environment and create a map representation of the surrounding environment. In the robot's autonomous environment traversal method, one branch is the frontier-based detection method. This method consumes more and more computing resources as the map expands and is not suitable for large-scale environment detection. Another branch is the random exploration method based on multiple rapidly-exploring randomized trees. This method uses the edge of the tree to search for the boundary, but the selection of the next exploration point is very demanding. This paper proposes an exploration point selection strategy based on the hybrid clustering method, which speeds up the RRT exploration method. Simulation experiments show that the improved RRT exploration method proposed in this paper takes less time to explore and build maps, especially in a large-scale mapping environment, which effectively improves the completeness and efficiency of mapping. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cluster analysis

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