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Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)

作者： Daosheng Huang Guanghui Xu Jie Wu Hui Xu Li-Xia Yang Zhi-Xiang Huang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9781728181813

ISBN: (纸本)9781728181820

The millimeter-Wave (mm-Wave) wideband integrated log-periodic antenna array based on multilayer PCB is proposed in this paper. The antenna array is simulated and designed to operate at the mm-Wave band of 32-47 GHz with the impedance bandwidth of 37.5%. Differential feeding is adopted to reduce the cross polarization, and EBG structure is used to improve the back lobe. The simulated maximum gain of the array is 11 dBi and the cross-polarization ratio is less than -40 dB. Due to its wide bandwidth, high gain and low cross polarization, the proposed array will be a suitable scheme for many mm-Wave applications.

关键词： Millimeter wave technology Nonhomogeneous media Broadband antennas Gain Wideband Antenna arrays Periodic structures

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A Novel FDTD Algorithm Based on the Vector and Scalar Potentials Equations 5

A Novel FDTD Algorithm Based on the Vector and Scalar Potent...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Liu, Zhipeng Xie, Guoda Wu, Bo Ren, Xingang Fang, Ming Huang, Zhixiang Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538671115

As the advance in nanotechnology, the length of electronic devices down to nano-scale structure. It is important to consider multi-scale phenomena ruled by the Maxwell's equation in the finite-difference time-domain (FDTD) simulation. This paper provides an alternate approach for solving the vector and scalar potentials (A and Φ) formulation of Maxwell's equations instead of the fields (E and H) which might suffer from low frequency breakdown problem. This new approach is more suitable for multi-scale problem since it is stable in the long wavelength regime which established the proposed method as a better algorithm in the electromagnetic simulation. © 2019 IEEE.

关键词： Maxwell equations

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PRISTA-Net: Deep Iterative Shrinkage Thresholding Network for Coded Diffraction Patterns Phase Retrieval

arXiv

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arXiv 2023年

作者： Liu, Aoxu Fan, Xiaohong Yang, Yin Zhang, Jianping The School of Mathematics and Computational Science Xiangtan University Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan411105 China The School of Mathematics and Computational Science Xiangtan University the Key Laboratory of Intelligent Computing & Information Processing the Ministry of Education Xiangtan411105 China The School of Mathematics and Computational Science Xiangtan University the National Center for Applied Mathematics in Hunan Xiangtan411105 China

The problem of phase retrieval (PR) involves recovering an unknown image from limited amplitude measurement data and is a challenge nonlinear inverse problem in computational imaging and image processing. However, many of the PR methods are based on black-box network models that lack interpretability and plug-and-play (PnP) frameworks that are computationally complex and require careful parameter tuning. To address this, we have developed PRISTA-Net, a deep unfolding network (DUN) based on the first-order iterative shrinkage thresholding algorithm (ISTA). This network utilizes a learnable nonlinear transformation to address the proximal-point mapping sub-problem associated with the sparse priors, and an attention mechanism to focus on phase information containing image edges, textures, and structures. Additionally, the fast Fourier transform (FFT) is used to learn global features to enhance local information, and the designed logarithmic-based loss function leads to significant improvements when the noise level is low. All parameters in the proposed PRISTA-Net framework, including the nonlinear transformation, threshold parameters, and step size, are learned end-to-end instead of being manually set. This method combines the interpretability of traditional methods with the fast inference ability of deep learning and is able to handle noise at each iteration during the unfolding stage, thus improving recovery quality. Experiments on Coded Diffraction Patterns (CDPs) measurements demonstrate that our approach outperforms the existing state-of-the-art methods in terms of qualitative and quantitative evaluations. Our source codes are available at https://***/liuaxou/PRISTA-Net. Copyright © 2023, The Authors. All rights reserved.

关键词： Mapping

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A Verlet Time-stepping Nodal DGTD Method for Electromagnetic Scattering and Radiation 5

A Verlet Time-stepping Nodal DGTD Method for Electromagnetic...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Wang, Yulong Zhao, Ran Huang, Zhixiang Wu, Xianliang Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538671115

In this paper, a discontinuous Galerkin time domain (DGTD) method is proposed to solve electromagnetic radiation and scattering problems. In this method, for the electromagnetic radiation problem, the dipole source excitation is introduced by the Total field / Scattering field (TF/SF) boundary condition. On the basis of TF/SF boundary condition, an equivalent principle (EP) based boundary condition is also introduced. For the electromagnetic scattering problem, the plane wave excitation is introduced by pure scattered field method. For all the cases, uniaxial perfectly matched layer (UPML) is used as the truncated boundary condition to enhance the reflection wave absorption. At the same time, the method uses nodal local basis function (for spatial discretization) and Verlet method (for time integration) to solve Maxwell equation. Numerical results show the effectiveness and accuracy of the algorithm. © 2019 IEEE.

关键词： Boundary conditions

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Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algorithm in Uplink Grant-Free NOMA 19

Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algo...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Zhang, Jian Bai, Shichao Xu, Lei Zhang, Hongwei Fang, Hongyu Li, Xiaohui Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei China

ISBN: (纸本)9781728105352

In the uplink grant-free non-orthogonal multiple access (NOMA) scenario, since the active user at the sender has a structured sparsity transmission characteristic, the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data. However, the existing compressive sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio (SNR) as the priori conditions, which greatly reduces the algorithm adaptability in multi-user detection. Therefore, an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit (CVA-SSAOMP) is proposed to realize multi-user detection in dynamic change communication scenario of channel state information (CSI). The proposed algorithm transforms the structured sparsity model into a block sparse model, and without the priori conditions above, the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation. The simulation results show that, compared with the traditional orthogonal matching pursuit (OMP) algorithm, subspace pursuit (SP) algorithm and cross validation aided block sparsity adaptive subspace pursuit (CVA-BSASP) algorithm, the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio (BER), and has the advantage of low-complexity. © 2019 IEEE.

关键词： Multiuser detection

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A Low SAR, Small size, High gain, Circularly polarized Antenna for Wearable Application 2

A Low SAR, Small size, High gain, Circularly polarized Anten...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Wang, Chao Zhang, Liang Cheng, Yi Li, XueMei Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Hefei Anhui230601 China

A planar, small size, high gain, low specific absorption rate (SAR) and circularly-polarized (CP) wearable antenna is proposed in this paper. The antenna is fabricated on a substrate with a dielectric constant of 3.5 with a thickness of 0.5 mm and sized at 42×42 mm only. Both the simulation results show that the overlap bandwidth of impedance and axial ratio of the proposed antenna is 13.7% (5.15-5.91 GHz). To isolate the antenna against the influence of the human body, a artificial magnetic conductor (AMC) plane is added on the reverse side of the radiator. The AMC structure effectively isolates the human body from the radiation of the antenna and reduces the specific absorption rate (SAR) of it by more than 96.1% at 5.5 GHz, which improves the antenna gain and the peak gain reaches 5.09 dBi at 5.5 GHz. The wearable performance of the antenna was analyzed, and it is observed that it can sustain good performance even under human body loading. Beside, the antenna has a small size, which makes it ideal for wearable applications. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Wearable antennas

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Component edge connectivity of hypercube-like networks

arXiv

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arXiv 2021年

作者： Liu, Dong Li, Pingshan Zhang, Bicheng Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education School of Mathematical and Computational Sicence Xiangtan University Hunan Xiangtan41105 China

As a generalization of the traditional connectivity, the g-component edge connectivity cλg(G) of a non-complete graph G is the minimum number of edges to be deleted from the graph G such that the resulting graph has at least g components. Hypercube-like networks (HL-networks for short) are obtained by manipulating some pairs of edges in hypercubes, which contain several famous interconnection networks such as twisted cubes, Möbius cubes, crossed cubes, locally twisted cubes. In this paper, we determine the (g + 1)-component edge connectivity of the n-dimensional HL-networks for g ≤ 2[n/2], n ≥ 8. Copyright © 2021, The Authors. All rights reserved.

关键词： Graph theory

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GK: A Graphormer Architecture Based Knowledge Graph Reasoning Model for Link Prediction

GK: A Graphormer Architecture Based Knowledge Graph Reasonin...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yueiia Wu Jian-tao Zhou Ministry of Education Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing College of Computer Science Inner Mongolia University National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Engineering Research Center of Ecological Big Data Hohhot China

Knowledge Graph has become a dominant research field in graph theory, but its incompleteness and sparsity hinder its application in various fields. Knowledge Graph Reasoning aims to alleviate these problems by deducing new knowledge or identifying false knowledge from existing knowledge. Recently, the Graph Convolution Network (GCN) based method is one of the most advanced methods to realize knowledge graph reasoning. However, it still suffers from some problems such as incomplete neighbor information aggregation and slow training speed. This paper proposes a knowledge graph reasoning model named GK for the link prediction task, which obtains better performance than existing GCN-based methods by introducing Graphormer into knowledge reasoning. The GK first proposes that nodes and their surroundings can be regarded as a hierarchical architecture that enables the model to capture more practical reasoning information to improve prediction accuracy. In addition, to accelerate the training speed of the model on the large-scale Knowledge Graph, we present a faster shortest path-finding method F-SPF in the edge coding process. Extensive experimental results show that the GK model can obtain the state-of-the-art prediction results of current GCN-based methods and can improve the training speed.

关键词： Training Knowledge engineering Knowledge graphs Predictive models Prediction algorithms Feature extraction Cognition

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A Hybrid Tourism Recommendation System Based on Multi-Objective Evolutionary Algorithm and Re-Ranking

SSRN

引用

SSRN 2022年

作者： Cao, Ruifen Li, Zijue Wei, Pijing Tian, Ye Zheng, Chunhou Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Computer Science and Technology Anhui University Heifei230601 China Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

The tourism recommendation system (TRS) can intelligently recommend the next attractions for users according to their historical visit records. To improve tourists’ travel experience, it is very important for TRS to select the attractions that users are interested in from a large number of attractions. Most tourism recommendation methods only consider accuracy as an evaluation index, which can no longer meet the needs of users who are increasingly seeking for diversified attractions. Actually, there is often a conflict between accuracy and diversity, and how to balance these two conflict objectives is a difficulty problem for recommendation system. In order to solve the problem, a hybrid recommendation model based on multi-objective optimization and re-ranking (MOEA/D-HRR) is proposed in this study. To overcome the limited predictive power of a single recommendation algorithm, MOEA/D-HRR mixes three different classical techniques by weighted summation of their recommended results, and then improve the diversity of the recommendation list by using the re-ranking algorithm based on Maximal Marginal Relevance (MMR). In addition, we construct a multi-objective optimization problem in which accuracy and diversity are formulated as two objectives, and use a multi-objective evolutionary algorithm (MOEA) to optimize the weights and parameter of the re-ranking algorithm. A lot of experiments on two public tourism datasets and a new tourism dataset were carried out. Experimental results showed that the model could provide users with diversified attractions while ensuring the accuracy of recommendation attraction. © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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RGB-T Saliency Detection via Robust Graph Learning and Collaborative Manifold Ranking 14th

RGB-T Saliency Detection via Robust Graph Learning and Colla...

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14th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 2019

作者： Sun, Dengdi Li, Sheng Ding, Zhuanlian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

Visual saliency detection inspired by brain cognitive mechanisms is an important component of computer vision, aiming at automatically highlight salient visual objects from the image background. In complex real scenarios, integrating multiple different yet complementary feature representations has been proved to be an effective way for boosting saliency detection performance. In this paper, we propose a novel collaborative algorithm for saliency detection by adaptively incorporating information from grayscale and thermal images. Specifically, we first construct an affinity graph model via robust graph learning to characterize the feature similarities and location relationships between two different image patches under each modal. Based on these affinity graphs, a collaborative manifold ranking method cross-modality consistent constraints is designed to effectively and efficiently infer the salient score for each patch. Moreover, we introduce a weight for each modality to describe the reliability, and integrate them into the graph-based manifold ranking scheme to achieve an adaptive weighted fusion of different source data. For optimization, we propose some iterative algorithms to efficiently solve the models with several subproblems. Experiments on the grayscale-thermal datasets demonstrate the superior performance of the new method over the state-of-the-art approaches. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Graphic methods

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