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AASRI International Conference on Applied Engineering Science, ICAES 2014

作者： Peng, M. Li, M.Q. Rong, B. Ding, Y. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781138026490

In this paper, a novel design of theWideband Bandstop Filter, based on Split Ring Resonators, (SRR) is proposed. The Defect Ground Structure (DGS) is achieved by opening the SRR-shaped slot in the ground plane, and the metal cylinder is added between micro-strip line and the ground. With the above two methods, the wideband bandstop characteristics can be realized. This proposed structure is simulated by the high frequency simulation software HFSS 13.0, and the effect on the performance of a wideband Band-stop Filter by adding a metal column is studied. The design of Band-stop Filter structure with three cascaded SRR-shaped DGS units is proposed. Both the simulated and measured results show that the attenuation at the resonance frequency center reaches −55 dB, and its relative bandwidth less than −10 dB is extended to 42% ranging from 5.6 GHz to 8.6 GHz. Moreover, the insertion loss of passband is limited to 1.2 dB. © 2015 Taylor & Francis Group, London.

关键词： Notch filters

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Vehicle appearance feature recognition based on image

Vehicle appearance feature recognition based on image

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2016 6th International Conference on Machinery,Materials,Environment,Biotechnology and Computer(MMEBC 2016)

作者： Deyang Shao Chao Xu Shixian Luo Bo Feng Long Jiao Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University Key Laboratory of Intelligent Computer & Signal Processing Ministry of EducationAnhui University

ISBN: (纸本)9781510828087

Now, the highway toll system still uses a single license plate recognition, this method has a problem of inaccurate identificationFor this kind of situation, this paper put forward to increase the appearance of the vehicle feature information and can improve the accuracy of recognitionIn this paper, we adopt the ORB algorithm to extract the exterior feature information of the vehicle and two-way matching、RANSAC algorithms to remove mismatching pointsAt the same time, we continue to iteration the scale parameter of the affine transformation and rotation angle at the matching point as a kind of judgment, which improves the robustness of the algorithm.

关键词： Feature information ORB RANSAC Affine transformation

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Comparative analysis of identification methods for wheat leaf diseases

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International Agricultural Engineering Journal 2016年第3期25卷 197-203页

作者： Zhang, D.Y. Xie, X.H. Liang, D. Huang, L.S. Zhang, X.Q. Teng, L. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University School of Electronic and Information Engineering Hefei Anhui230601 China

How to fast, accurately and robustly recognize wheat diseases, particularly for those diseases with mild-to-moderate severity, is a challenge for prevention and control of crop disease timely. In this study, image processing technique was applied to segment the infected regions of disease leaves. Twenty disease features were extracted, and eighteen larger weight features were selected by Relief-F algorithm to generate the models of Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Back Propagation Neural Network (BPNN). Subsequently, these models were used to identify two kinds of wheat diseases, namely, wheat stripe rust and powdery mildew. Total 136 samples, including 68 training samples and 68 test samples with different infection severities were used to study the recognition capabilities of the three models. Results showed that high predictive accuracies in identification of two wheat diseases with varying severity for all three models. Overall accuracy of RVM was 89.71%, which was superior to 83.82% of SVM and inferior to 92.64% of BPNN. Meanwhile, the recognition accuracies of SVM, RVM and BPNN models for mild-to-moderate disease were 83.33%, 88.33% and 91.67%, respectively. The prediction time of RVM was less than those of SVM and BPNN, with differences as large as 7.96 and 31.68 times, respectively. Therefore, RVM appeared to be the most suitable for real-time identifying wheat leaf diseases among the three models, which can provide important technical support for wheat diseases management.

关键词： Support vector machines

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A novel dual passband lowpass filter based on U-shaped DGS

A novel dual passband lowpass filter based on U-shaped DGS

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International Conference on Multimedia, Communication and computing Application, MCCA 2014

作者： He, H.Q. Li, M.Q. Ding, Y. Chang, H.X. Zhao, F.L. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HefeiAnhui China

ISBN: (纸本)9781138027756

In this paper, a novel design of the dual passband lowpass filter based on the Defect Ground Structure (DGS) is proposed. The defect ground structure (DGS) is achieved by opening a set of asymmetric U-shaped slot in the ground plane and the microstrip line using a U-strip resonator. This proposed structure is simulated by the high frequency simulation software HFSS 13.0. In comparison with the filter without U-shaped DGS, the proposed filter has low insertion loss and its frequency ranges from 8.4GHz to 12.7GHz, signal restrains from 2.7dB to 14dB. The simulated and measured results show good agreement and validate the proposed approach. © 2015 Taylor & Francis Group, London.

关键词： Bandpass filters

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Image Hiding Selection for Large Touch Screen System

Image Hiding Selection for Large Touch Screen System

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IEEE International Conference on Information and Automation

作者： Qihan Jiang Lei Cheng Rongbin Xu Jianguo Wu Ying Xie Department of Computer Science and Technology Anhui University Hefei Anhui230601 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui 230039 China

ISBN: (纸本)9781509041039

Various kinds of information in large touch screen system need to be protected by various reasons so we need to hide them. One kind of image hiding selection algorithm is proposed here. The steps are as follows, the carrier image and secret message is obtained by pre-processing to get a most hiding matrix suitable for image and message, then secret message is hidden into the carrier image by using Kim's method. The final hidden image and the original carrier image is almost the same from the naked eye. Finally, a few tests are carried out and the test results suggest that the hidden effect of the whole scheme is good.

关键词： Image Hiding Exploiting Modification Direction Large Touch Screen

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From standard alpha-stable Lévy motions to horizontal visibility networks: dependence of multifractal and Laplacian spectrum

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Journal of Statistical Mechanics: Theory and Experiment 2018年第5期2018卷

作者： Hai-Long Zou Zu-Guo Yu Vo Anh Yuan-Lin Ma Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan 411105 People's Republic of China School of Electrical Engineering and Computer Science Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia Author to whom any correspondence should be addressed. School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

In recent years, researchers have proposed several methods to transform time series (such as those of fractional Brownian motion) into complex networks. In this paper, we construct horizontal visibility networks (HVNs) based on the -stable Lévy motion. We aim to study the relations of multifractal and Laplacian spectrum of transformed networks on the parameters and of the -stable Lévy motion. First, we employ the sandbox algorithm to compute the mass exponents and multifractal spectrum to investigate the multifractality of these HVNs. Then we perform least squares fits to find possible relations of the average fractal dimension , the average information dimension and the average correlation dimension against using several methods of model selection. We also investigate possible dependence relations of eigenvalues and energy on , calculated from the Laplacian and normalized Laplacian operators of the constructed HVNs. All of these constructions and estimates will help us to evaluate the validity and usefulness of the mappings between time series and networks, especially between time series of -stable Lévy motions and HVNs.

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Robust low-rank tensor factorization by cyclic weighted median

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Science China(Information Sciences) 2015年第5期58卷 145-155页

作者： MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Computing Hong Kong Polytechnic University Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications

Low-rank tensor factorization(LRTF) provides a useful mathematical tool to reveal and analyze multi-factor structures underlying data in a wide range of practical applications. One challenging issue in LRTF is how to recover a low-rank higher-order representation of the given high dimensional data in the presence of outliers and missing entries, i.e., the so-called robust LRTF problem. The L1-norm LRTF is a popular strategy for robust LRTF due to its intrinsic robustness to heavy-tailed noises and outliers. However, few L1-norm LRTF algorithms have been developed due to its non-convexity and non-smoothness, as well as the high order structure of data. In this paper we propose a novel cyclic weighted median(CWM) method to solve the L1-norm LRTF problem. The main idea is to recursively optimize each coordinate involved in the L1-norm LRTF problem with all the others fixed. Each of these single-scalar-parameter sub-problems is convex and can be easily solved by weighted median filter, and thus an effective algorithm can be readily constructed to tackle the original complex problem. Our extensive experiments on synthetic data and real face data demonstrate that the proposed method performs more robust than previous methods in the presence of outliers and/or missing entries.

关键词： tensor factorization low-rank weighted median filter tensorface

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Two weight Zpk -codes, p odd prime

arXiv

引用

arXiv 2017年

作者： Shi, Minjia Sepasdar, Zahra Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province230039 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China School of Mathematical Sciences of Anhui University Hefei230601 China Department of Pure Mathematics Ferdowsi University of Mashhad P. O. Box 1159 Mashhad91775 Iran CNRS/LTCI Telecom ParisTech University of Paris-Saclay Paris75 013 France Department of Mathematics Faculty of Science King Abdulaziz University Jeddah21589 Saudi Arabia

We show that regular homogeneous two-weight Zpk -codes where p is odd and k ≥ 2 with dual Hamming distance at least four do not exist. The proof relies on existence conditions for the strongly regular graph built on ... 详细信息

关键词： Hamming distance

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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

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An improved reference point sampling method on Pareto optimal front

An improved reference point sampling method on Pareto optima...

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Congress on Evolutionary Computation

作者： Cheng He Linqiang Pan Hang Xu Ye Tian Xingyi Zhang Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei CN Department of Computer Science Xiamen University Xiamen Fujian China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei Anhui China

ISBN: (纸本)9781509006243

In this paper, we propose a sampling approach of reference points used for performance metrics of multi-objective evolutionary algorithms. Traditional reference point sampling methods, such as the Das and Dennis method, usually sample the reference points via a set of uniformly distributed weight vectors generated on an ideal hyper-plane in objective space, which however often ignore the geometric shape of a specific Pareto front. Therefore, we propose a novel reference point sampling approach by taking the specific shape of the Pareto optimal front to be tackled into account for measuring the performance of multi-objective evolutionary algorithms. The performance of the proposed reference point sampling method against the other two state-of-the-art sampling methods is tested on six test instances in various conditions, which clearly demonstrate the effectiveness and superiority of the proposed sampling method.

关键词： Sampling methods Shape Convergence Evolutionary computation Optimization Euclidean distance

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