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arXiv 2019年

作者： Tu, Zhengzheng Xia, Tian Li, Chenglong Wang, Xiaoxiao Ma, Yan Tang, Jin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Institute of Physical Science and Information Technology Anhui University Hefei China

Image saliency detection is an active research topic in the community of computer vision and multimedia. Fusing complementary RGB and thermal infrared data has been proven to be effective for image saliency detection. In this paper, we propose an effective approach for RGB-T image saliency detection. Our approach relies on a novel collaborative graph learning algorithm. In particular, we take superpixels as graph nodes, and collaboratively use hierarchical deep features to jointly learn graph affinity and node saliency in a unified optimization framework. Moreover, we contribute a more challenging dataset for the purpose of RGB-T image saliency detection, which contains 1000 spatially aligned RGB-T image pairs and their ground truth annotations. Extensive experiments on the public dataset and the newly created dataset suggest that the proposed approach performs favorably against the state-of-the-art RGB-T saliency detection methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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On Error Performance and Concatenated Coding of Polar Codes in AWGN Channels

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IOP Conference Series: Materials Science and Engineering 2020年第7期768卷

作者： Jing Jin Rui Deng Tiansheng Liu Liping Li Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) Anhui University Hefei China Department of Electronic Engineering and Information Science University of Science and Technology Hefei China

In additive white Gaussian noise (AWGN) channels, construction of polar codes is needed for every operating signal-to-noise ratio (SNR). Recently, the proposal of the design-SNR reduces the computation effort in constructing polar codes. In this paper, we prove that although the BER performance of the design-SNR construction is not affected, the packet-error-rate (PER) performance is degraded compared with the point-by-point construction. Therefore, a concatenation scheme is proposed to improve the degraded PER performance. Results show the validity of the proposed concatenation scheme when employing the design-SNR construction.

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Local averaging type a posteriori error estimates for the nonlinear steady-state Poisson-Nernst-Planck equations

arXiv

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arXiv 2020年

作者： Yang, Ying Shen, Ruigang Fang, Mingjuan Shu, Shi School of Mathematics and Computational Science Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guilin University of Electronic Technology Guilin541004 China School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan411105 China School of Mathematics and Computational Science Guilin University of Electronic Technology GuilinGuangxi541004 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan411105 China

The a posteriori error estimates are studied for a class of nonlinear stead-state Poisson-Nernst-Planck equations, which are a coupled system consisting of the Nernst-Planck equation and the Poisson equation. Both the global upper bounds and the local lower bounds of the error estimators are obtained by using a local averaging operator. Numerical experiments are given to confirm the reliability and efficiency of the error estimators. Copyright © 2020, The Authors. All rights reserved.

关键词： Finite element method

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Sliding Mode Control of Fractional-Order Delayed Memristive Chaotic System with Uncertainty and Disturbance

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Communications in Theoretical Physics 2017年第12期67卷 741-748页

作者：丁大为刘芳芳陈辉王年梁栋 Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University School of Electronics and Information Engineering Anhui University

In this paper, a simplest fractional-order delayed memristive chaotic system is proposed in order to control the chaos behaviors via sliding mode control strategy. Firstly, we design a sliding mode control strategy for the fractionalorder system with time delay to make the states of the system asymptotically stable. Then, we obtain theoretical analysis results of the control method using Lyapunov stability theorem which guarantees the asymptotic stability of the noncommensurate order and commensurate order system with and without uncertainty and an external disturbance. Finally,numerical simulations are given to verify that the proposed sliding mode control method can eliminate chaos and stabilize the fractional-order delayed memristive system in a finite time.

关键词： fractional-order system memristive system time delay sliding mode control stability theorem

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A computationally-efficient sandbox algorithm for multifractal analysis of large-scale complex networks with tens of millions of nodes

arXiv

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arXiv 2020年

作者： Ding, Yuemin Liu, Jin-Long Li, Xiaohui Tian, Yu-Chu Yu, Zu-Guo School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science Queensland University of Technology BrisbaneQLD4000 Australia Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan411105 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan Hubei430081 China

The fractality of complex networks has attracted much attention with extensive investigations over the last 15 years. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful tool to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. One of the widely used methods for fractal analysis is box-covering. It uses the minimum number of covering boxes to calculate the fractal dimension of complex networks, and is known to be NP-hard. More severely, in comparison with fractal analysis algorithms, MFA algorithms have much higher computational complexity. Among various MFA algorithms for complex networks, the sandbox MFA algorithm behaves with the best computational efficiency. However, the existing sandbox algorithm is still computationally expensive. Thus, so far it has only been applied to small-scale complex networks of the size of about tens of thousands of nodes. It becomes challenging to implement the MFA for large-scale networks with tens of millions of nodes. It is also not clear whether or not MFA results can be improved by a largely increased size of a theoretical network. To tackle these challenges, a computationally-efficient sandbox algorithm (CESA) is presented in this paper for MFA of large-scale networks. Distinct from the existing sandbox algorithm that uses the shortest-path distance matrix to obtain the required information for MFA of complex networks, our CESA employs the breadth-first search (BFS) technique to directly search the neighbor nodes of each layer of center nodes, and then to retrieve the required information. Our CESA's input is a sparse data structure derived from the compressed sparse row (CSR) format designed for compressed storage of the adjacency matrix of large-scale network. A theoretical analysis reveals that the CESA reduces the time complexity of the existing sandbox algorithm from cubic to quadratic, and also improves the space complexity from quadratic

关键词： Computational efficiency

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Hybrid Control of Delay Induced Hopf Bifurcation of Dynamical Small-World Network

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Journal of Shanghai Jiaotong university(Science) 2017年第2期22卷 206-215页

作者：丁大为张肖芸王年梁栋 Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electronics and Information Engineering Anhui University

In this paper, we focus on the Hopf bifurcation control of a small-world network model with time-delay. With emphasis on the relationship between the Hopf bifurcation and the time-delay, we investigate the effect of time-delay by choosing it as the bifurcation parameter. By using tools from control and bifurcation theory, it is proved that there exists a critical value of time-delay for the stability of the model. When the time-delay passes through the critical value, the model loses its stability and a Hopf bifurcation occurs. To enhance the stability of the model, we propose an improved hybrid control strategy in which state feedback and parameter perturbation are used. Through linear stability analysis, we show that by adjusting the control parameter properly, the onset of Hopf bifurcation of the controlled model can be delayed or eliminated without changing the equilibrium point of the model. Finally, numerical simulations are given to verify the theoretical analysis. © 2017, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.

关键词： Hopf bifurcation hybrid control small-world network bifurcation control

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Fast Frequency Sweep Analysis of a Dielectric Rough Surface by Maehly Approximation

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IEEE Journal on Multiscale and Multiphysics Computational Techniques 2017年 2卷 224-227页

作者： Bao, Ran Wang, Anqi Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

An efficient method for simulating electromagnetic scattering from a dielectric rough surface over a frequency band is proposed. The method is based on the Chebyshev series and the Maehly approximation. The tapered plane wave is chosen as the incident wave to avoid the artificial edge diffraction caused by the finite length of the simulated rough surface. The Gaussian rough surface is considered. Good agreement between the Maehly approximation and the exact results obtained by the method of moments (MoM) is found. The numerical results show that the Maehly approximation is superior to the MoM in terms of the CPU time required. © 2017 IEEE.

关键词： Method of moments

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Multifractal temporally weighted detrended partial cross-correlation analysis of two non-stationary time series affected by common external factors

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Physica A: Statistical Mechanics and its Applications 2021年 573卷

作者： Bao-Gen Li Dian-Yi Ling Zu-Guo Yu Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Electrical Engineering and Computer Science Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

When common factors strongly influence two cross-correlated time series recorded in complex natural and social systems, the results will be biased if we use multifractal detrended cross-correlation analysis (MF-DXA) without considering these common factors. In order to better study the time series of such cases, we extend the multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA) proposed by our group (Wei et al., 2017) and propose multifractal temporally weighted detrended partial cross-correlation analysis (MF-TWDPCCA) to quantify intrinsic power-law cross-correlation of two non-stationary time series affected by common external factors in this paper. To test the performance of MF-TWDPCCA, we apply it and multifractal partial cross-correlation analysis (MF-DPXA) proposed by Qian et al. (2015) on simulated series. Numerical tests on artificially simulated series demonstrate that MF-TWDPCCA can more accurately detect the intrinsic cross-correlations for two simultaneously recorded series than MF-DPXA and MF-TWXDFA. To further show the utility of MF-TWDPCCA, we apply it on time series from stock markets and find that there exists significantly multifractal power-law cross-correlation between stock returns. In addition, a new partial cross-correlation coefficient is defined to quantify the level of intrinsic cross-correlation between two time series.

关键词： Partial cross-correlation Multifractal temporally weighted detrended partial cross-correlation analysis Partial cross-correlation coefficient

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Channel estimation with systematic polar codes

arXiv

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arXiv 2018年

作者： Li, Liping Xu, Zuzheng Hu, Yanjun Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education of China Anhui University China

Study of polar codes in fading channels is of great importance when applying polar codes in wireless communications. Channel estimation is a fundamental step for communication to be possible in fading channels. For both systematic and non-systematic polar codes, construction of them is based on an information set and the known frozen bits. Efficient implementation of systematic and non-systematic polar codes exists. When it comes to channel estimation or channel tracking, additional pilot symbols are inserted in the codeword traditionally. In this paper, to improve the performance of polar codes in the finite domain, pilot symbols are selected from the coded symbols themselves. In order to keep the existing efficient structure of polar code encoding, pilot selection is critical since not all selections can reuse the existing structure. In this paper, two pilot selections denoted as Uneven Pilot Selection (UEPS) and Even Pilot Selection (EPS) are proposed, which do not change the efficient polar encoding structure. The proposed UEPS and EPS is proven to satisfy the efficient construction condition. The performance of EPS is shown in this paper to outperform both the UEPS and the traditional pilot insertion scheme. Simulation results are provided which verify the performance of the proposed pilot selection schemes. Copyright © 2018, The Authors. All rights reserved.

关键词： Fading channels

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A Method of Channel Capacity Optimization Based on Dynamically Adjusted Inertia Weight Acceleration Factor in Cognitive Sensing Network

A Method of Channel Capacity Optimization Based on Dynamical...

引用

International Conference on Software Engineering Research, Management and Applications (SERA)

作者： Yanjun Hu Dongdong Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538658871

The optimization of channel capacity in cognitive sensor networks is a complicated optimization problem. The traditional gradient search method based on the analysis has more restrictions on the objective function, and high complexity, and can not determine the convergence. Aiming at the inherent problems of the traditional gradient search algorithm, the particle swarm optimization(PSO) with simple and easy to implement, distributed computing and fast convergence speed can be used to solve the problem of channel capacity optimization. It is difficult to balance the global search with the local search by adopting a standard particle swarm algorithm with fixed algorithm parameters, which can not solve the premature convergence problem that may occur. The specific meaning of each parameter of the algorithm is analyzed in this paper, and an improved particle swarm optimization algorithm based on dynamic adjustment of inertia weight acceleration factor(DWAPSO) is proposed, and the improved particle swarm optimization algorithm is applied to the optimization of channel capacity in cognitive sensor networks. The simulation results show that the improved channel capacity optimization algorithm(DWAPSO-CA) can speed up the convergence rate, increase the system capacity and get a lower bit error rate.

关键词： Channel capacity particle swarm algorithm Bit error rate system capacity Particle swarm optimization Inertial forces speedup factor Search methods SEARCHING ALGORITHM Converge Distributed computing

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