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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shangyu Lu Guohui Yang Kuang Zhang Yingsong Li School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

Based on the equivalent circuit model of PIN diode and the full wave simulation method of CST software, the system performance of finite large energy selective surface (ESS) is simulated and analyzed when the number of cells is small. The simulation results show that the working performance of ESS will be degraded by the slight surface deformation caused by external force but not fail completely. Therefore, in the practical application of ESS, attention should be paid to avoid deformation caused by external force extrusion, which will reduce the shielding performance of ESS. The simulation results provide reference value for the practical design and application of energy selective surface.

关键词： Analytical models Deformation Surface waves PIN photodiodes Simulation System performance Force

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Study on Pedestrian Evacuation Model Base on Reinforcement Learning

SSRN

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SSRN 2024年

作者： Rui, Zhu Hu, Jun Ling, Fan Qi, Zhang Juan, Wei School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Key Laboratory of Interior Layout Optimization and Security Institutions of Higher Education of Sichuan Province Chengdu Normal University Chengdu611130 China School of Intelligent Manufacturing Chengdu Technological University Chengdu611730 China Key Laboratory of Multidimensional Data Sensing and Intelligent Information Processing Dazhou Key Laboratory Dazhou635000 China

This paper proposed a pedestrian evacuation model combined with reinforcement learning in order to study how to better guide pedestrians to complete evacuation in specific indoor scenes. This model introduced the way of establishing a scene in cellular automata and formulated reward rules according to the characteristics of the scene. It fitted the psychological activities of pedestrians in the actual evacuation process and trained the strategy of pedestrians at the overall level through the Q-learning algorithm from the reinforcement learning area. A speed control mechanism combined with real statistical data was introduced to simulate the speed attenuation. A simulation platform was built to compare the evacuation conditions under different scenarios and the different total numbers of pedestrians. The research showed that the model could automatically realize the exit selection function of pedestrians and part of conformity behavior. In the same evacuation scenario, this model could show adaptability for the different total numbers of pedestrians. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Fast θ -Maruyama scheme for stochastic Volterra integral equations of convolution type: mean-square stability and strong convergence analysis

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Computational and Applied Mathematics 2023年第3期42卷

作者： Wang, Mengjie Dai, Xinjie Yu, Yanyan Xiao, Aiguo Hunan Key Laboratory for Computation and Simulation in Science and Engineering National Center for Applied Mathematics in Hunan Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan Xiangtan411105 China School of Mathematics and Statistics Yunnan University Yunnan Kunming650504 China

In this paper, a fast θ-Maruyama method is proposed for solving stochastic Volterra integral equations of convolution type with singular and Hölder continuous kernels based on the sum-of-exponentials approximation. Furthermore, the average storage O(N) and the calculation cost O(N2) of θ-Maruyama scheme are reduced to O(log N) and O(Nlog N) for T 1 or O(log 2N) and O(Nlog 2N) for T≈ 1 , respectively, which implies that the fast θ-Maruyama scheme is confirmed to improve the computational efficiency of the θ-Maruyama method. Under the local Lipschitz and linear growth conditions, strong convergence of the given numerical scheme are obtained. Then, for the linear test equation, we show the asymptotic behavior of solutions in mean square sense. Further, we obtain the explicit structure of the stability matrices and some numerical results of the mean-square stability for the fast θ-Maruyama method applied to the linear test equation. Finally, some numerical experiments are also given to illustrate the effectiveness of the method. © 2023, The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional.

关键词： Computational efficiency

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Selecting Discriminative Features for Fine-Grained Visual Classification 5th

Selecting Discriminative Features for Fine-Grained Visual Cl...

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5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Xu, Qin Li, Linyang Chen, Qian Luo, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

ISBN: (纸本)9783030414030

Fine-grained visual classification is a challenging task because of intra-class variation and inter-class similarity. Most fine-grained models predominantly focus on discriminative region localization which can effectively solve the intra-class variation, but ignore global information and the problem of inter-class similarity which easily leads to overfitting on specific samples. To address these issues, we develop an end-to-end model based on selecting discriminative features for fine-grained visual classification without the help of part or bounding box annotations. In order to accurately select discriminative features, we integrate effective information from different receptive fields to enhance the quality of features, then the features of discriminative regions detected by anchors and the whole image’s feature are jointly processed for classification. Besides, we propose a new loss function to optimize the model to find discriminative regions and prevent overfitting in the particular sample, which can simultaneously solve the problems of intra-class variation and inter-class similarity. Comprehensive experiments show that the proposed approach is superior to the state-of-the-art methods on CUB-200-2011, Stanford Cars and FGVC-Aircraft datasets. © Springer Nature Switzerland AG 2020.

关键词： Classification (of information)

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Vector Field-Guided Circumnavigation for an Unmanned Surface Vehicle With Boundary and Obstacle Constraints

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IEEE Transactions on Emerging Topics in computing 2025年

作者： Wu, Nailong Wang, Jigang Wang, Yueying He, Shuping Donghua University College of Information Science and Technology Shanghai201620 China Donghua University Engineering Research Center of Digitized Textile & Apparel Technology Ministry of Education Shanghai201620 China Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electrical Engineering and Automation Hefei230601 China

This article aims to tackle the challenge of rapid target circumnavigation by unmanned surface vehicles (USVs) under boundary and obstacle constraints through leveraging an emerging computing architecture specifically tailored for unmanned systems. Owing to the underactuation of USV dynamic systems and the presence of various time-varying surface disturbances, attaining rapid and accurate position control along with maneuverability poses a significant challenge to USVs. Therefore, when an USV maneuvers around a target in a confined search area with obstacles, it is essential for the guidance law to consider collision risks and environmental disturbances. This paper proposes a modified Lyapunov vector field with heading deviation compensation to circle the target in complex search regions. The vector field is designed to increase the radial velocity of the USV and accelerate convergence towards the target circle during the pursuit phase. By combining the proposed Lyapunov vector field with a boundary vector field, the USV can swiftly avoid boundaries and dynamic obstacles and then continue circling the target. The proposed computing architecture extends the application scope of the target circumnavigation to practical water surface environments, which is validated by extensive simulations and rigorous experiments. © 2025 IEEE.

关键词： Unmanned surface vehicles

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Accelerating evolutionary neural architecture search via multi-fidelity evaluation

arXiv

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arXiv 2021年

作者： Yang, Shangshang Tian, Ye Xiang, Xiaoshu Peng, Shichen Zhang, Xingyi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

Evolutionary neural architecture search (ENAS) has recently received increasing attention by effectively finding high-quality neural architectures, which however consumes high computational cost by training the architecture encoded by each individual for complete epochs in individual evaluation. Numerous ENAS approaches have been developed to reduce the evaluation cost, but it is often difficult for most of these approaches to achieve high evaluation accuracy. To address this issue, in this paper we propose an accelerated ENAS via multifidelity evaluation termed MFENAS, where the individual evaluation cost is significantly reduced by training the architecture encoded by each individual for only a small number of epochs. The balance between evaluation cost and evaluation accuracy is well maintained by suggesting a multi-fidelity evaluation, which identifies the potentially good individuals that cannot survive from previous generations by integrating multiple evaluations under different numbers of training epochs. For high diversity of neural architectures, a population initialization strategy is devised to produce different neural architectures varying from ResNetlike architectures to Inception-like ones. Experimental results on CIFAR-10 show that the architecture obtained by the proposed MFENAS achieves a 2.39% test error rate at the cost of only 0.6 GPU days on one NVIDIA 2080TI GPU, demonstrating the superiority of the proposed MFENAS over state-of-the-art NAS approaches in terms of both computational cost and architecture quality. The architecture obtained by the proposed MFENAS is then transferred to CIFAR-100 and ImageNet, which also exhibits competitive performance to the architectures obtained by existing NAS approaches. The source code of the proposed MFENAS is available at https://***/DevilYangS/MFENAS/.MSC Codes 68W50, 68T07 © 2021, CC BY.

关键词： Convolutional neural networks

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Hamiltonian Boundary Value Methods (HBVMs) for functional differential equations with piecewise continuous arguments

arXiv

引用

arXiv 2024年

作者： Gurioli, Gianmarco Wang, Weijie Yan, Xiaoqiang Università degli Studi di Firenze Florence Italy School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan411105 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan411105 China

In this paper, a class of high-order methods to numerically solve Functional Differential Equations with Piecewise Continuous Arguments (FDEPCAs) is discussed. The framework stems from the expansion of the vector field associated with the reference differential equation along the shifted and scaled Legendre polynomial orthonormal basis, working on a suitable extension of Hamiltonian Boundary Value Methods. Within the design of the methods, a proper generalization of the perturbation results coming from the field of ordinary differential equations is considered, with the aim of handling the case of FDEPCAs. The error analysis of the devised family of methods is performed, while a few numerical tests on Hamiltonian FDEPCAs are provided, to give evidence to the theoretical findings and show the effectiveness of the obtained resolution *** Codes 65L05, 65L03, 65L06, 65P10 Copyright © 2024, The Authors. All rights reserved.

关键词： Ordinary differential equations

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Long Video Micro-expression Spotting Based On OCC Theory

Long Video Micro-expression Spotting Based On OCC Theory

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： BingTong Liu ZheYuan Zhang Ju Zhou HanPu Wang Tong Chen Institute of Legal Psychology and Intelligent Computing Southwest University Chongqing China Chongqing Key Laboratory of Non-Linear Circuit and Intelligent Information Processing Chongqing China School of Electronic and Information Engineering Southwest University Chongqing China

The generation of micro-expression (ME) is unconscious and unaffected by human subjective consciousness. It can reveal hidden emotions in humans, which has important applications in the domains of psychological diagnosis, lie detection, and so on. ME detection, which aims to locate ME apex frames in long videos, is the foundation of ME recognition. In this paper, we propose a ME detection method based on One-Class Classification (OCC) theory for long videos. The method is the first to use neutral expression frames to detect MEs, which addresses the problem of insufficient training samples in ME detection. We design a geometric motion feature based on the prior knowledge from the FACS and utilize it in conjunction with the features extracted by CNN to train separate one-class classifiers for ME detection. Finally, we evaluate the proposed method on publicly available datasets CASME I, CASME II, SAMM, and a mixed database comprising data from the three datasets, to verify the feasibility of the proposed method in both single-database and cross-database ME detection. The experimental results show that our method outperforms three other ME detection methods, demonstrating its ability to more accurately locate ME apex frames in long videos.

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An Improved Differential Evolution Algorithm Integrating the Plant Evolutionary Strategy

SSRN

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SSRN 2024年

作者： Zhang, Xiaoming Cheng, Hongwei Li, Jun Li, Tingjuan Zhang, Panpan Tian, Ye Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Qinghai Institute of Science and Technology Information Xining810008 China School of Computer Science and Technology Anhui University Hefei230601 China

Differential evolution algorithm (DE) and their variants often encounter a decrease in population diversity and convergence rate along with the evolution, resulting in local optima and premature convergence. To address this issue, this paper proposes an improved differential evolution integrating the plant evolutionary strategy, named DEPES, leveraging the exploitation capability of DE and the exploration capability of the plant population distribution evolutionary strategy. First, a tri-subpopulation optimization framework with a mutation strategy is introduced to cope with diversity maintenance, convergence enhancement, and local optima a Cauchy mutation operator based on plant population distribution evolutionary model is employed to enhance the exploration capability of the mutation strategy. Second, a parameter control strategy is performed on the superior and inferior solutions to balance the exploitation and exploration of the population. Third, a covariance matrix-based crossover strategy is designed to minimize interference from local population information, consequently generating high-quality solutions. The superior efficiency of DEPES is fully verified by comparing it with advanced DE-based variants and other algorithms on the IEEE CEC2020 test suite and engineering design problems. © 2024, The Authors. All rights reserved.

关键词： Covariance matrix

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Determining the covering radius of all generalized Zetterberg codes in odd characteristic

arXiv

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arXiv 2024年

作者： Shi, Minjia Li, Shitao Helleseth, Tor Özbudak, Ferruh Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China School of Mathematical Sciences Anhui University Anhui Hefei230601 China Department of Informatics University of Bergen Bergen Norway Faculty of Engineering and Natural Sciences Sabancı University Istanbul34956 Turkey

For an integer s ≥ 1, let Cs(q0) be the generalized Zetterberg code of length qs0 + 1 over the finite field Fq0 of odd characteristic. Recently, Shi, Helleseth, and Özbudak (IEEE Trans. Inf. Theory 69(11): 7025-7048, 2023) determined the covering radius of Cs(q0) for (formula presented) (mod 8), and left the remaining case as an open problem. In this paper, we develop a general technique involving arithmetic of finite fields and algebraic curves over finite fields to determine the covering radius of all generalized Zetterberg codes for (formula presented) (mod 8), which therefore solves this open problem. We also introduce the concept of twisted half generalized Zetterberg codes of length (formula presented) , and show the same results hold for them. As a result, we obtain some quasi-perfect codes. Copyright © 2024, The Authors. All rights reserved.

关键词： Turbo codes

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