检索结果-内蒙古大学图书馆

A broadband ±45◦ dual-polarized magneto-electric dipole antenna for 2G/3G/LTE/5G/WiMAX applications

Progress In Electromagnetics Research C 2018年 86卷 153-165页

作者： Lu, Zongzheng Sun, Yufa Zhu, Haoran Huang, Fei Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230601 China

A novel broadband &#1.7;45◦ dual-polarized magneto-electric (ME) dipole antenna is proposed for 2G/3G/LTE/5G (3.3–3.6 GHz)/WiMAX applications. The proposed antenna has Γ-shaped feeding strips to impart a wide impeda... 详细信息

A novel broadband ±45◦ dual-polarized magneto-electric (ME) dipole antenna is proposed for 2G/3G/LTE/5G (3.3–3.6 GHz)/WiMAX applications. The proposed antenna has Γ-shaped feeding strips to impart a wide impedance bandwidth for its special structure. Stable antenna gain and radiation pattern are realized by using a rectangular box-shaped reflector instead of planar one. The antenna is fabricated and measured. The measured results show that a common impedance bandwidth is 83% with standing-wave ratio (SWR) ≤ 1.5 from 1.59 to 3.83 GHz and port-to-port isolation larger than 25 dB within the bandwidth. The measured antenna gains vary from 8 to 1..8 dBi and from 8 to 1..6 dBi for port 1.and port 2, respectively. The antenna has nearly symmetrical radiation patterns with low back lobe radiation both in horizontal and vertical planes, and broadside radiation patterns with narrow beam can also be obtained. The proposed antenna can be used for multiband base stations in next generation communication systems. © 201., Electromagnetics Academy. All rights reserved.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

A compact multiband omnidirectional GNSS antenna for artillery projectile applications

引用

Progress In Electromagnetics Research C 2016年 62卷 149-156页

作者： Liu, Weiwei Sun, Yufa Zhou, Dong Hu, Shaoqi Yang, Ming Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

A compact multiband omnidirectional antenna for the reception of GNSS signals on artillery projectiles is designed in this paper. The proposed antenna consists of a metallic cone comprising a T-shaped monopole. It exhibits a broad bandwidth from 1.22 GHz to 1.28 GHz and from 1.44 GHz to 1.75 GHz, covering GPS L1. Galileo E2-L1.E1. GLONASS G1.and G2, CNSS B1.and B3. Measured results show that an omnidirectional radiation pattern is achieved, and the non-circularity in the azimuthal plane (xy-plane) is less than 2 dB for all the desired bands. Then the measured 6 dB beamwidth is about 1.0◦ in the presence of a finite 20 millimeters (mm) radius ground plane. Such an antenna has the potential to be easily used for small artillery projectiles. © 201., Electromagnetics Academy. All rights reserved.

关键词： Monopole antennas

来源：评论

学校读者我要写书评

暂无评论

The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

The Downlink Performance of Massive MIMO Systems under Diffe...

引用

第二届材料科学应用与能源材料国际研讨会

作者： Ziju Huang Hui Zhi Feiyue Wang Key Lab of Computing Intelligent and Signal Processing(Ministry of Education) Anhui University

In the scenario of time division duplexing(TDD) massive multiple-input multiple-output(MIMO) system,when there is pilot contamination(PC) in the uplink,different pilot allocation schemes will affect the results of the uplink channel *** the channel estimation results are used for downlink transmission precoding,which will further affects the downlink *** paper analyses the impact of different pilot allocation(PA) schemes on downlink *** theoretical analysis,the system downlink signal to interference plus noise ratio(SINR) and spectral efficiency expressions of different pilot allocation schemes are obtained *** simulation results show that the pilot allocation schemes with cell grouping is better than the schemes without cell *** SINR increases as the number of cell grouping increases,and the spectrum efficiency increases first and then decreases as the number of cell grouping increases.

关键词： TDD The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

来源：评论

学校读者我要写书评

暂无评论

On alpha-mean of Kullback-Leibler divergences for subspace selection

On alpha-mean of Kullback-Leibler divergences for subspace s...

引用

201. 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 201., Jointly with the 201. 7th International Conference on Natural Computation, ICNC'1.

作者： Chen, Si-Bao Wang, Hai-Xian Zhang, Xing-Yi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781612841816

Fisher's linear discriminant analysis (FLDA) is one of the most well-known linear subspace selection methods. However, FLDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. Recent results show that maximizing the geometric mean or harmonic mean of Kullback-Leibler (KL) divergences of class pairs can significantly reduce this problem. In this paper, to further reduce the class separation problem, the alpha-mean of divergences as a framework is proposed for subspace selection, with arithmetic mean, geometric mean and harmonic mean as special cases. We named it the maximization of the alpha-mean of all pairs of KL divergences (MAMD) criterion. A quasi-Newton method is applied to solve the optimization problem. Experiments on synthetic data and two datasets in UCI machine learning repository show the validity of MAMD. © 201. IEEE.

关键词： Newton-Raphson method

来源：评论

学校读者我要写书评

暂无评论

Manifold feature extraction for video based on locally linear embedding

Manifold feature extraction for video based on locally linea...

引用

International Conference on Computer Science and education

作者： Fu, Maosheng Xu, Qin Kong, Min Luo, Bin Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Computer Science and Technology West Anhui University Anhui Lu'an 237012 China

ISBN: (纸本)9781424460052

Locally linear embedding (LLE) is an elegant nonlinear method for feature extraction and manifold learning, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. However, LLE algorithm fails when it is directly applied to video with multi-shot. In this paper, video manifold feature is defined firstly, and then using LLE we extract video manifold feature through adding virtual frames on an enriched set. The proposed manifold feature extraction method is applied to shot transition and video trajectories. The video manifold feature description gives a new tool for video analysis. ©201. IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A novel approch for clustering of Chinese text based on concept hierarchy

A novel approch for clustering of Chinese text based on conc...

引用

IEEE International Conference on Cognitive Informatics

作者： Zhao, Peng Geng, Huan-Tong Cai, Qing-Sheng Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9781424404759

After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic classify dictionary as background knowledge to clustering of Chinese text. It adopts a hierarchical coding system which reflects concept relevance among different words and uses Vector Space Model based on concept hierarchy to represent Chinese text. The experimental results show this approach is more effective than traditional text clustering method based on keywords set. © 2006 IEEE.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

SES: Bridging the Gap between Explainability and Prediction of Graph Neural Networks 40

SES: Bridging the Gap between Explainability and Prediction ...

引用

40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Huang, Zhenhua Li, Kunhao Wang, Shaojie Jia, Zhaohong Zhu, Wentao Mehrotra, Sharad Anhui University Hefei China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Hefei China Amazon Research Seattle United States University of California Irvine Irvine United States

ISBN: (纸本)9798350317152

Despite the Graph Neural Networks' (GNNs) pro-ficiency in analyzing graph data, achieving high-accuracy and interpretable predictions remains challenging. Existing GNN interpreters typically provide post-hoc explanations disjointed from GNNs' predictions, resulting in misrepresentations. Self-explainable GNNs offer built-in explanations during the training process. However, they cannot exploit the explanatory outcomes to augment prediction performance, and they fail to provide high-quality explanations of node features and require additional processes to generate explainable subgraphs, which is costly. To address the aforementioned limitations, we propose a self-explained and self-supervised graph neural network (SES) to bridge the gap between explainability and prediction. SES comprises two processes: explainable training and enhanced predictive learning. During explainable training, SES employs a global mask generator co-trained with a graph encoder and directly produces crucial structure and feature masks, reducing time consumption and providing node feature and subgraph explanations. In the enhanced predictive learning phase, mask-based positive-negative pairs are constructed utilizing the ex-planations to compute a triplet loss and enhance the node representations by contrastive learning. Extensive experiments demonstrate the superiority of SES on multiple datasets and tasks. SES outperforms baselines on real-world node classification datasets by notable margins of up to 2.59% and achieves state-of-the-art (SOTA) performance in explanation tasks on synthetic datasets with improvements of up to 3.0%. Moreover, SES delivers more coherent explanations on real-world datasets, has a fourfold increase in Fidelity+ score for explanation quality, and demonstrates faster training and expla-nation generating times. To our knowledge, SES is a pioneering GNN to achieve SOTA performance on both explanation and prediction tasks. © 2024 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

引用

201. 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 201.

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD. ©201. IEEE.

关键词： Discriminant analysis

来源：评论

学校读者我要写书评

暂无评论

A full-rate wireless cooperative relay transmission scheme with low detection complexity

引用

Journal of Computational Information Systems 2012年第13期8卷 5279-5285页

作者： Zhang, Hongwei Liu, Yanru Zhang, Ye Li, Xiaohui Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

To achieve low detection complexity and full-rate wireless cooperative transmissions, pre-coding and cyclic delay diversity (CDD) techniques are fully considered and properly combined for a two-path successive relay network with multiple relay nodes in this paper. Firstly, the symbols to be transmitted at source node are encoded with linear complex field coding methods, and then these coded symbols are divided into two data streams. Both streams are transmitted to two groups of relay nodes respectively during two consecutive time slots. After having been amplified and forwarded by relay nodes using CDD ways, all transmit signals are received by the destination node finally. At receiver, only two symbols are needed to be jointly detected in each transmission process, the complexity is low. Simulation results show that the proposed scheme can achieve full-rate cooperative relay transmissions and obtain high diversity gains of the distributed wireless systems. © 201. by Binary Information Press.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

引用

Journal of Electronic Science and Technology 2010年第2期8卷 183-186页

作者： De-Xiang Zhang Xiao-Pei Wu Zhao Lv Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition （EMD） algorithm and Teager energy operator （TEO） is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions （IMFs）, which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Index Terms----Empirical mode decomposition endpoint detection noisy speech Teager energy operator.

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：