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arXiv 2018年

作者： Xiao, Fen Deng, Wenzheng Peng, Liangchan Cao, Chunhong Hu, Kai Gao, Xieping Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Hunan411105 China

Salient object detection is a fundamental problem and has been received a great deal of attentions in computer vision. Recently deep learning model became a powerful tool for image feature extraction. In this paper, we propose a multi-scale deep neural network (MSDNN) for salient object detection. The proposed model first extracts global high-level features and context information over the whole source image with recurrent convolutional neural network (RCNN). Then several stacked deconvolutional layers are adopted to get the multi-scale feature representation and obtain a series of saliency maps. Finally, we investigate a fusion convolution module (FCM) to build a final pixel level saliency map. The proposed model is extensively evaluated on four salient object detection benchmark datasets. Results show that our deep model significantly outperforms other 12 state-of-the-art approaches. Copyright © 2018, The Authors. All rights reserved.

关键词： Convolution

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Reversible data hiding in encrypted images with Two-MSB prediction 10

Reversible data hiding in encrypted images with Two-MSB pred...

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10th IEEE International Workshop on Information Forensics and Security, WIFS 2018

作者： Puyang, Yi Yin, Zhaoxia Qian, Zhenxing Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei230601 China Department of Computer Science Purdue University West lafayette47906 United States Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200072 China

ISBN: (纸本)9781538665367

In recent years, reversible data hiding in encrypted images (RDHEI) that embeds additional data into the encrypted image content has received more and more attention. In previous RDHEI methods, there is no one considering the correlation between neighboring pixels. In this paper, to better explore the correlation between neighbor pixels, a novel reversible data hiding method in encrypted images with two-MSB (MSB and second MSB) prediction is proposed. After analyzing the original image content and detecting all the possible prediction errors, we encrypt the original image content using the bitwise exclusive-or (XOR) operation and highlight prediction error based on the error location binary map. Finally, all available pixels are embedded with additional data by two-MSB substitution. In our method, reversibility, separability and error-free data extraction are realized. The experimental results show that the proposed method providing a higher embedding rate and better quality of directly decrypted image compared with other start-of-the-art methods. © 2018 IEEE.

关键词： Pixels

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A Novel Multiple-traces Electric Field/Combined Field Integral Equation for Electromagnetic Modeling of Microstrip Objects

A Novel Multiple-traces Electric Field/Combined Field Integr...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yv Long Wang Ran Zhao Zhi Xiang Huang Jun Hu Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University School of Electronic Engineering University of Electronic Science and Technology of China (UESTC)

In this paper, a new multiple-traces electric field/combined field integral equation (MT-EF/CFIE) is proposed for the electromagnetic modeling of microstrip objects. Different from traditional EFIE-PMCHWT method, this new multiple-traces method decomposes the original microstrip object into two independent domains i.e., the exterior region (free space) and interior region (microstrip), and enforces the Robin transmission conditions (TCs) on the interface between exterior and interior regions to ensure the continuity of fields. In comparison to the traditional EFIE-PMCHWT, this new MT-EF/CFIE has a better convergence property. Because the continuity of fields is ensured by TCs, the exterior and interior regions can be discretized by non-conformal meshes, which improves the flexibility and efficiency of the proposed methods substantially.

关键词： Microstrip Microstrip antenna arrays Dielectrics Integral equations Electromagnetic scattering Convergence

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3D fresnel field computing method based on its propagation reversibility

3D fresnel field computing method based on its propagation r...

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Chinese Society for Optical Engineering Conferences, CSOE 2016

作者： Zhang, Kai Wang, Xiangxiang Tan, Shengxia Shen, Chuan Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui230039 China

ISBN: (纸本)9781510610118

There are many 3D data structures for computing diffraction field, the description based on 3D point-cloud is the elemental method of other descriptions, the diffraction field of 3D scene can be thought as the superposition of the diffraction field of each sampled light point and other descriptions can be thought as grouping with point-cloud by different way. The paper focuses on devising a computation method of 3D Fresnel field which is based on Fresnel diffraction field propagation reversibility. The proposed method combines the reversibility of Fresnel propagation and the requirement of sampling spacing by Nyquist criterion, i.e. to find the best space positions to optimize the number of sampling points and the reconstruction for the 3D Fresnel field. The method can be applied to reduce the computational complexity and improve computational efficiency. © 2017 SPIE.

关键词： Computational efficiency

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Localization Optimization Algorithm of Maximum Likelihood Estimation Based on Received signal Strength 9

Localization Optimization Algorithm of Maximum Likelihood Es...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Qiang Chen Jingjing Zhang Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781509038237;9781509038220

In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received signal strength error to node localization precision. This paper presents an indoor localization algorithm based on received signal strength to select anchor nodes. Compared with the traditional localization algorithm, this scenario not only improve the localization accuracy, but also reduce the calculation complexity of nodes. The simulation results show that the average error of the proposed method is less than 0.15 m. Moreover, when there are a large number of anchor nodes, the computational complexity is effectively reduced. Verification result verifies the effectiveness and reliability of the algorithm.

关键词： localization received signal strength(RSS) maximum likelihood estimation(MLE) least squares threshold

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Speaker Recognition Based on the Improved Double-Threshold Endpoint Algorithm and Multistage Vector Quantization 9

Speaker Recognition Based on the Improved Double-Threshold E...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Jingjing Zhang Qiang Chen Peipei Tu Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781509038237;9781509038220

The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algorithm for this phenomenon, which effectively avoids the problem of missing detection. Then, Mel Frequency Cepstral Coefficients(MFCC) is used to extract the characteristic parameters of the speech signal, and the multistage vector quantization is used to quantify the characteristic parameters. Experimental results show that, the proposed algorithm improves the recognition rate of the text-independent speaker recognition system by 8.7%, and it also confirms that the longer the training speech is, the higher the recognition rate will be.

关键词： the multistage vector quantization MFCC double-threshold endpoint detection method missing detection characteristic parameters

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Nonlinearity in the dark: Broadband terahertz generation with extremely high efficiency

arXiv

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arXiv 2019年

作者： Fang, Ming Shen, Nian-Hai Sha, Wei E.I. Huang, Zhixiang Koschny, Thomas Soukoulis, Costas M. Ames Laboratory U.S. DOE and Department of Physics and Astronomy Iowa State University AmesIA50011 United States Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China FORTH Heraklion Crete71110 Greece

Plasmonic metamaterials and metasurfaces offer new opportunities in developing high performance terahertz emitters/detectors beyond the limitations of conventional nonlinear materials. However, simple meta-atoms for second-order nonlinear applications encounter fundamental trade-offs in the necessary symmetry-breaking and local-field enhancement due to radiation damping that is inherent to the operating resonant mode and cannot be controlled separately. Here we present a novel concept that eliminates this restriction obstructing the improvement of terahertz generation efficiency in nonlinear metasurfaces based on metallic nano-resonators. This is achieved by combing a resonant dark-state metasurface, which locally drives nonlinear SRRs in the near field, with a specific spatial symmetry that enables destructive interference of the radiating linear moments of the SRRs, and perfect absorption via simultaneous electric and magnetic critical coupling of the pump radiation to the dark mode. Our proposal allows eliminating linear radiation damping, while maintaining constructive interference and effective radiation of the nonlinear components. We numerically demonstrate a giant second-order nonlinear susceptibility ∼ 10−11 m/V, one order improvement compared to previously reported split-ring-resonator metasurface, and correspondingly, two orders of magnitude enhanced terahertz energy extraction should be expected with our configuration under the same conditions. Our study offers a paradigm of high efficiency tunable nonlinear meta-devices and paves the way to revolutionary terahertz technologies and optoelectronic nanocircuitry. Copyright © 2019, The Authors. All rights reserved.

关键词： Terahertz waves

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Uplink Supportive Number of Users in Massive MIMO Systems 9

Uplink Supportive Number of Users in Massive MIMO Systems

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Chao Wang Peng Ma Chaochao Jia Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Technology and Innovation Department Shanghai Research Center for Wireless Communication

ISBN: (纸本)9781509038237;9781509038220

The supportive number of users achieving the maximum sum rate is studied in uplink massive MIMO systems for zero-forcing(ZF) and maximum-ratio combining(MRC). We obtain the lower bound of the achievable rate of each user for ZF and MRC receivers with any finite number of base station(BS) antennas, respectively. By this theoretical result, this paper will focus on the supportive number of users which was constrained with the minimum achievable rate. Through analyzing the optimal problem of maximizing the overall sum rate, we obtain the expression of optimal number of users and present the user scheduling algorithm for achieving the maximized sum rate. The numerical results show that the massive MIMO systems can improve the supportive number of users, and ZF receivers can support more number of users than MRC under the same condition.

关键词： large number of antennas achievable uplink rate supportive number of users massive MIMO

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A multigrid-reduction-in-time solver with a new two-level convergence for unsteady fractional Laplacian problems

arXiv

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arXiv 2019年

作者： Yue, Xiaoqiang Pan, Kejia Zhou, Jie Weng, Zhifeng Shu, Shi Tang, Juan Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China School of Mathematics and Statistics HNP-LAMA Central South University Changsha410083 China School of Mathematical Sciences Fujian Province University Key Laboratory of Computation Science Huaqiao University Quanzhou362021 China

The multigrid-reduction-in-time (MGRIT) technique has proven to be successful in achieving higher run-time speedup by exploiting parallelism in time. The goal of this article is to develop and analyze a MGRIT algorithm, using FCF-relaxation with time-dependent time-grid propagators, to seek the finite element approximations of unsteady fractional Laplacian problems. The multigrid with line smoother proposed in [L. Chen, R. H. Nochetto, et al., Math. Comp. 85 (2016) 2583–2607] is chosen to be the spatial solver. Motivated by [B. S. Southworth, SIAM J. Matrix Anal. Appl. 40 (2019) 564–608], we provide a new temporal eigenvalue approximation property and then deduce a generalized two-level convergence theory which removes the previous unitary diagonalization assumption on the fine and coarse time-grid propagators required in [X. Q. Yue, S. Shu, et al., Comput. Math. Appl. 78 (2019) 3471–3484]. Numerical computations are included to confirm the theoretical predictions and demonstrate the sharpness of the derived convergence upper bound. Copyright © 2019, The Authors. All rights reserved.

关键词： Finite element method

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An Adaptive Spectrum Allocation Algorithm in Ultra-Dense Network

An Adaptive Spectrum Allocation Algorithm in Ultra-Dense Net...

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International Conference on Communication Software and Networks, ICCSN

作者： Jun Zhu Chaochao Jia Chao Wang Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Hefei China Technology and Innovation Department Shanghai Research Center for Wireless Communication Shanghai China

In this paper, we propose a novel method to adaptively adjust the parameter threshold used in overlapping frequency. We verify the performance of the proposed algorithm from the system simulation. Compared with the traditional network planning scheme which needs setting parameters manually, the optimal threshold is adaptively adjusted according to the distribution of the users. The simulation results show that the algorithm can improve the signal-to-interference-plus-noise-ratio (SINR) performance of users and the cell throughput when the users are distributed in the edge of cell coverage which owns the same optimization result as traditional optimization method. So the algorithm can effectively solve the decrease problem of spectral efficiency when the threshold in frequency overlap is set unreasonable and also save a lot of labour cost on setting parameters.

关键词： Interference signal to noise ratio Throughput Clustering algorithms Bandwidth Radio spectrum management Resource management

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