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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Wenjie Ding Guoda Xie Zhixiang Huang Education of Anhui Province. Anhui Province Key Laboratory of Target Recognition and Feature Extraction (Luan Anhui 237000 China) Ministry of Education. the Key Laboratory of Intelligent Computing and Signal Processing Hefei China Key Laboratory of Electromagnetic Environmental Sensing (Hefei 230601 China) Anhui Province Anhui University Anhui university Hefei China

Combining the spatial filtering (SF) technique with FDTD(2, q) method (2 and q denote the temporal differential order and spatial differential order, respectively), a novel SF-FDTD(2, q) method with more relaxed Courant-Friedrichs-Lewy (CFL) condition is proposed and used for solving 3D time-dependent Schrödinger equation. Then, the correctness of the SF-FDTD(2, $q$ ) method is validated by calculating eigenfrequencies of the 3D quantum well model.

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Efficient CDI-FDTD Method for Modelling Graphene-Based Structures

Efficient CDI-FDTD Method for Modelling Graphene-Based Struc...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jiale Liu Guoda Xie Zhixiang Huang Education of Anhui Province. Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan Anhui China Ministry of Education. the Key Laboratory of Intelligent Computing and Signal Processing Hefei China Anhui Province Anhui University. Key Laboratory of Electromagnetic Environmental Sensing Hefei China Anhui university Hefei China

This paper presents a novel approach for calculating graphene-based structures in the complying divergence implicit finite-difference time-domain (CDI-FDTD) method. To begin, the differential iteration formula of graphene structure in the CDI-FDTD method is derived utilizing the auxiliary-differential-equation (ADE) method. Next, the transmission characteristics of an infinite graphene sheet in an open space are investigated by conducting simulation analyses within the CDI-FDTD framework, considering various magnetostatic or electrostatic biases. Finally, the simulation results were compared with analytical solutions and the results obtained from traditional FDTD methods, confirming the unconditional stability and reliability of the proposed method.

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Remaining Useful Life Prediction of Bearing via a Double Attention-Based Deep Neural Network

Remaining Useful Life Prediction of Bearing via a Double Att...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Yongkang Liu Donghui Pan Haifeng Zhang Kai Zhong Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei Anhui China Institutes of Physical Science and Information Technology Anhui University Hefei Anhui China

Predicting the remaining useful life (RUL) of bearings is important for the secure running and reducing maintenance costs of rotating machinery. In this article, a novel feature extraction and RUL prediction framework of bearing is proposed by utilizing time-frequency representations (TFRs) and deep neural network with double attention (DA-DNN). Firstly, TFRs are employed to extract the degradation features associated with RUL prediction, which can effectively cope with the non-stationary properties of bearing vibration data. The reduced dimensional TFRs are then used as the DA-DNN model input. Afterwards, DA-DNN is developed by employing the double attention structure to extract the key degradation features more efficiently. The dual-attention structure has ability to capture the degradationrelated features from two aspects of channel attention and spatial attention, which enables the network to focus on high RUL-relevant information. Finally, the experimental results demonstrate the effectiveness of DA-DNN, which shows higher performance in terms of prediction accuracy compared to other deep learning (DL) methods.

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Machine learning prediction of network dynamics with privacy protection

arXiv

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arXiv 2022年

作者： Xia, Xin Su, Yansen Lü, Linyuan Zhang, Xingyi Lai, Ying-Cheng Zhang, Hai-Feng The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei230601 China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

Predicting network dynamics based on data, a problem with broad applications, has been studied extensively in the past, but most existing approaches assume that the complete set of historical data from the whole network is available. This requirement presents a great challenge in applications, especially for large, distributed networks in the real world, where data collection is accomplished by many clients in a parallel fashion. Often, each client only has the time series data from a partial set of nodes and the client has access to only partial timestamps of the whole time series data and partial structure of the network. Due to privacy concerns or license related issues, the data collected by different clients cannot be shared. To accurately predict the network dynamics while protecting the privacy of different parties is a critical problem in the modern time. Here, we propose a solution based on federated graph neural networks (FGNNs) that enables the training of a global dynamic model for all parties without data sharing. We validate the working of our FGNN framework through two types of simulations to predict a variety of network dynamics (four discrete and three continuous dynamics). As a significant real-world application, we demonstrate successful prediction of State-wise influenza spreading in the USA. Our FGNN scheme represents a general framework to predict diverse network dynamics through collaborative fusing of the data from different parties without disclosing their privacy. © 2022, CC BY.

关键词： Forecasting

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A Circularly Polarized Antenna for GPS L1 band with U-Shaped-Like Strips

A Circularly Polarized Antenna for GPS L1 band with U-Shaped...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Lulu Meng Zhixiang Huang Yingsong Li School of Electronic and Information Engineering Anhui University Hefei 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

A U-shaped-like parasitic strip loading antenna is proposed and designed, which can work in L1 band of GPS with circular polarization (CP) characteristics. The antenna consists of ground plane, dielectric, radiation patch and U-shaped-like parasitic strips using a simple coaxial feed probe. The asymmetric U-shaped-like strips are to realize CP. The simulation and optimization results for the modeled directional CP antenna show that the axial ratio bandwidth is 10MHz and the impedance bandwidth is 30MHz, which can meet the requirements for GPS L1 band.

关键词： Polarization Loading Bandwidth Directive antennas Probes Loaded antennas Optimization

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Belief-selective Propagation Detection for MIMO Systems

arXiv

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arXiv 2022年

作者： Zhou, Wenyue Shen, Yifei Li, Liping Huang, Yongming Zhang, Chuan You, Xiaohu National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211189 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China

Compared to the linear MIMO detectors, the Belief Propagation (BP) detector has shown greater capabilities in achieving near optimal performance and better nature to iteratively cooperate with channel decoders. Aiming at real applications, recent works mainly fall into the category of reducing the complexity by simplified calculations, at the expense of performance sacrifice. However, the complexity is still unsatisfactory with exponentially increasing complexity or required exponentiation operations. Furthermore, due to the inherent loopy structure, the existing BP detectors persistently encounter error floor in high signal-to-noise ratio (SNR) region, which becomes even worse with calculation approximation. This work aims at a revised BP detector, named Belief-selective Propagation (BsP) detector by selectively utilizing the trusted incoming messages with sufficiently large a priori probabilities for updates. Two proposed strategies: symbol-based truncation (ST) and edge-based simplification (ES) squeeze the complexity (orders lower than the Original-BP), while greatly relieving the error floor issue over a wide range of antenna and modulation combinations. For the 16-QAM 8 × 4 MIMO system, the B(1, 1) BsP detector achieves more than 4 dB performance gain (@BER = 10−4) with roughly 4 orders lower complexity than the Original-BP detector. Trade-off between performance and complexity towards different application requirement can be conveniently obtained by configuring the ST and ES parameters. © 2022, CC BY.

关键词： Belief propagation

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A Da-Shaped Slotted Circularly-Polarization Antenna for 5G Applications

A Da-Shaped Slotted Circularly-Polarization Antenna for 5G A...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Lulu Meng Zhixiang Huang Yingsong Li College of Electronic and Information Engineering Anhui University Hefei 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

This paper proposes a Da-shaped slotted antenna, where the Chinese culture is integrated into the antenna design to achieve an artistic antenna that can be used in 5G communication system. The designed antenna has circular polarization characteristic, which is composed of ground plane, dielectric layer and metal sheet A engraved with Da-shaped slot, and a U-shaped wall (metal sheet B). A simple L-shaped feed probe is used to improve the working bandwidth of the antenna. A U-shaped metal sheet B is considered to improve antenna gain and axial ratio bandwidth. The simulation and optimization results show that the axial ratio bandwidth is 2.30-2.71GHz, and the impedance bandwidth is 2.44-2.7GHz, both of which can cover operating frequency in the range of 2.515-2.675GHz of 5G.

关键词： Polarization Slot antennas 5G mobile communication Metals Bandwidth Directive antennas Antenna feeds

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Pyramid Convolution and Multi-Frequency Spatial Attention for Fine-Grained Visual Categorization

SSRN

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SSRN 2022年

作者： Xu, Qin Li, Yun Zhang, Mengquan Tao, Zhifu Luo, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China School of Big Data and Statistics Anhui University Hefei230601 China

Learning diverse detailed feature is crucial for fine-grained visual categorization (FGVC). However, most of existing methods for FGVC use the standard convolution for feature extraction which leads to the loss of many subtle but important features. Besides, in the existing attention models for FGVC, the features are aggregated by a simple global average pooling operation, which is unable to characterize complex feature information. To address these problems, we propose pyramid convolution and multi-frequency spatial attention (PCMFSA) for FGVC. To capture spatial context dependencies of different levels and avoid the loss of the subtle features, pyramid convolution, which uses convolution kernels with various sizes, is introduced in the backbone network. To reduce the influence of background noise and obtain diverse fine-grained feature information, we propose multi-frequency spatial attention (MFSA) module, in which two channel-wise grouping operations are designed and discrete cosine transform (DCT) in the frequency domain is adopted to enhance features of different spatial positions. Moreover, to mine more valuable regions, peak suppression is used to suppress high-response regions after MFSA. A large number of experimental results show that our method achieves state-of-the-art results on four popularly FGVC datasets. © 2022, The Authors. All rights reserved.

关键词： Convolution

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Robust 3D phase retrieval via compressed support detection from snapshot diffraction pattern

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Computers in Biology and Medicine 2024年 177卷 108644-108644页

作者： Zhang, Cheng Zhang, Liru Zhang, Ru Chen, Mingsheng Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Province Hefei230601 China Department of Electronic Engineering Tsinghua University Beijing100084 China School of Integrated Circuits Anhui University Anhui Province Hefei230601 China Anhui Provincial High-performance Integrated Circuit Engineering Research Center Anhui University Anhui Province Hefei230601 China

Traditional multislice iterative phase retrieval (MIPR) from snapshot two-dimensional measurements suffers from the two limitations of pre-defined support and iterative stagnation. To eliminate the requirements for priori knowledge of support masks, this paper proposes a multislice iterative phase retrieval algorithm based on compressed support detection and hybrid input-output algorithm (CSD-MIPR-HIO). The CSD-MIPR-HIO algorithm firstly uses compressed support detection to adaptively detect the support masks of each plane from single 2D diffraction intensity, and then uses a hybrid input-output (HIO) iterative algorithm for MIPR. The proposed method breaks the limitations of traditional MIPR algorithms on priori knowledge of support masks and achieve high-quality reconstruction in noisy environments. Numerical and optical experiments confirm the feasibility, superiority, and robustness of our proposed CSD-MIPR-HIO method. © 2024 Elsevier Ltd

关键词： Iterative methods

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A Radiation Performance Improvement Method of Extremely Low Frequency Acoustics Promoted Antenna

A Radiation Performance Improvement Method of Extremely Low ...

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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Junwei Qi Chenwei Zhang Yingsong Li Zhixiang Huang Tian Hong Loh Kwok L. Chung College of Information and Communications Engineering Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Electromagnetic and Eletrochemical Technologies Department National Physical Laboratory Middlesex UK School of Computer Science and Engineering Huizhou University P. R. China

In this paper, Q-value theory of conventional antennas is used to analyze reasons of low radiation performance of acoustics promoted antennas, where we modify the radiating structure of existing acoustics promoting antenna using the simulations to get the required improvement on radiation performance. The simulation experiments are carried out in the finite element simulation software Comsol Multiphysics to analyze the radiating performance.

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