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

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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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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Social Routing Based on Location Preference Prediction in DTN 11

Social Routing Based on Location Preference Prediction in DT...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： GuiZhu Wang LuJie Yan Lei Zheng Jian Tao Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (纸本)9781538605349;9781538605332

In modern society, with the pad, smart phones and other wireless devices have a large number of wireless communication interface, people carry these devices that act as network nodes, the random movement of such a network has many characteristics of social networks. The social DTN also has many human social characteristics, such as high predictability and high similarity, so in this paper, we focus on effective routing among different regions. As for the real world, we can adjust the Spray strategy according to the regional prediction and the similarity of the encounter nodes to reduce the noneffective duplicate and decrease the consumption of networks *** results show that compared with spray and wait routing, this algorithm could not only improve the delivery rate but also significantly reduce the average latency of network.

关键词： DTN spray and wait routing social network location preference prediction

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Singular Value Decomposition Compressed Ghost Imaging Based on Non-negative Constraints 11

Singular Value Decomposition Compressed Ghost Imaging Based ...

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2019第十一届数字图像处理国际会议

作者： Cheng Zhang Jun Tang Yuanyuan Zhu Meiqin Wang Qianwen Chen Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630758

Compressed ghost imaging can effectively enhance the quality of original image from far fewer measurements,but due to the non-negativity of the measurement matrix,the recover quality is thus *** this paper,singular value decomposition compressed ghost imaging is proposed;First,the singular value decomposition be used to decompose the measurement matrix,and then the optimized measurement matrix and measurements are used to recover the original *** experiments verify the superiority of our proposed singular value decomposition compression ghost imaging method.

关键词： ghost imaging compressed ghost imaging singular value decomposition compressed ghost imaging

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Probabilistic Routing Algorithm Based on Transmission Capability of Nodes in DTN 11

Probabilistic Routing Algorithm Based on Transmission Capabi...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Guizhu Wang Lei Zheng Lujie Yan Hui Zhang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (纸本)9781538605349;9781538605332

Delay Tolerant Network(DTN) is a network of intermittent connectivity, and for most of the time there is no end-to-end full path between nodes. This is a huge challenge for the efficient transmission of packets from the source to the destination node. In order to solve this problem, we combine the actually situation of the network, consider the difference of nodes,and propose the concept of node transmission *** a reasonable assessment of node transmission capacity and combined with the traditional probabilistic routing, this paper proposes a probabilistic routing algorithm based on the node transmission capability(PROPHET-TC), which makes the selection of the next hop node more reasonable and efficient, and compensate the deficiency of the traditional probabilistic routing in selecting the next hop node. Simulation results show that compared with Epidemic routing and probabilistic routing, the proposed algorithm can improve the delivery rate and reduce the overhead of the network.

关键词： Delay Tolerant Networks Node difference Probabilistic routing Transmission capacity

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Degradation-Trend-Aware Deep Neural Network with Attention Mechanism for Bearing Remaining Useful Life Prediction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2997-3011页

作者： Liu, Yongkang Pan, Donghui Zhang, Haifeng Zhong, Kai Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education School of Mathematical Sciences Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China

Remaining useful life (RUL) prediction of bearings has extraordinary significance for prognostics and health management (PHM) of rotating machinery. RUL prediction approaches based on deep learning have been dedicated to finding a nonlinear mapping relationship between nonstationary monitoring data and RUL. However, most existing approaches pay little attention to the degradation trend of diverse health stages of bearing and lack the discriminative power of crucial degradation features, resulting in the loss of some important information associated with RUL. To address this challenge, this article proposes a novel RUL prediction framework based on degradation-trend-aware deep neural network with attention mechanism (DTADAN). First the multidirection features with evident degradation trend are extracted via the analysis of bearing vibration signal from both time-domain and time-frequency domain. Next, the deep neural network architecture with attention mechanism is utilized to adaptively learn the critical degradation features beneficial for RUL prediction. Distinct from the existing approaches, the proposed framework is able to dynamically extract key degradation features of the bearing including degradation trend information and effectively fuse multidirection information to improve RUL prediction accuracy. The performance of the proposed approach is evaluated via case studies on XJTU-SY bearing dataset and PRONOSTIA bearing dataset. Compared with other state-of-the-art approaches, the proposed framework has better predictive accuracy and robustness. Additionally, interpretable analysis is provided to reveal the process of model learning and data characteristics, and the analysis results are helpful in guiding model learning. © 2020 IEEE.

关键词： Deep neural networks

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A recursive calculating algorithm for higher-order cumulants over sliding window and its application in speech endpoint detection

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Chinese Journal of Acoustics 2015年第4期34卷 436-449页

作者： LUO Yaqin WU Xiaopei L Zhao PENG Kui GUI Yajun The Key Laboratory of Intelligent Computing & Signal Processing Anhui University

Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is proposed. Then it is applied to the speech endpoint detection. Furthermore, endpoint detection is carried out with the feature of energy. Experimental results show that both the computational efficiency and the robustness against noise of the proposed algorithm are improved remarkably compared with traditional algorithm. The average prob- ability of correct point detection （Pc-point） of the proposed voice activity detection （VAD） is 6.07% higher than that of G.729b VAD in different noisy at different signal-noise ratios （SNRs） environments.

关键词： A recursive calculating algorithm for higher-order cumulants over sliding window and its application in speech endpoint detection over

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A Dynamic Transformer Network for Vehicle Detection

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IEEE Transactions on Consumer Electronics 2025年

作者： Tian, Chunwei Liu, Kai Zhang, Bob Huang, Zhixiang Lin, Chia-Wen Zhang, David Harbin Institute of Technology School of Computer Science and Technology Harbin15001 China Macao Special Administrative Region of China PAMI Research Group University of Macau 999078 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Hefei230601 China National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu Taiwan School of Data Science Shenzhen518172 China

Stable consumer electronic systems can assist traffic better. Good traffic consumer electronic systems require collaborative work between traffic algorithms and hardware. However, performance of popular traffic algorithms containing vehicle detection methods based on deep networks via learning data relation rather than learning differences in different lighting and occlusions is limited. In this paper, we present a dynamic Transformer network for vehicle detection (DTNet). DTNet utilizes a dynamic convolution to guide a deep network to dynamically generate weights to enhance adaptability of an obtained detector. Taking into relations of different information account, a mixed attention mechanism based channel attention and Transformer is exploited to strengthen relations of channels and pixels to extract more salient information for vehicle detection. To overcome the drawback of difference in an image account, a translation-variant convolution relies on spatial location information to refine obtained structural information for vehicle detection. Experimental results illustrate that our DTNet is competitive for vehicle detection. Code of the proposed DTNet can be obtained at https://***/hellloxiaotian/DTNet. © 2025 IEEE.

关键词： Dynamic convolution Hybrid Attention Mechanism Transformer Vehicle Detection

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Multilevel Characteristic Basis Function Method with ACA for Accelerated Solution of Electrically Large Scattering Problems

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第3期35卷 449-454页

作者： Li Chenlu Sun Yufa Wang Zhonggen Wang Guohua Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University College of Electrical and Information Engineering Anhui University of Science and Technology

The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.

关键词： multilevel characteristic basis function method(MLCBFM) adaptive cross approximation(ACA) characteristic basis functions(CBFs) electromagnetic scattering

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