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Long-Time Coherent Integration for Weak Maneuvering Target Detection and High-Order Motion Parameter Estimation Based on Keystone Transform

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IEEE Transactions on Signal processing 2016年第15期64卷 4013-4026页

作者： Huang, Penghui Liao, Guisheng Yang, Zhiwei Xia, Xiang-Gen Ma, Jing-Tao Ma, Jingting National Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Shanghai Engineering Center for Micro-Satellites Shanghai201203 China Beijing Huahang Radio Measurement Institute Beijing100013 China

In the airborne or spaceborne radar applications, prolonging the coherent integration time is one of the effective methods to improve the radar detection ability of a weak maneuvering target, whereas the coherent integration performance may degrade due to the complex range migration (RM) and Doppler frequency migration (DFM) effects. In this paper, detection and motion parameter estimation for a weak maneuvering target with the third-order RM and DFM are considered. Firstly, Keystone transform is applied to compensate the linear range walk. Then, the matched filtering processing is performed in the range-frequency and azimuth-time domain to eliminate the residual coupling effects between range and azimuth. Finally, a well-focused image of a moving target is obtained, and three motion parameters, i.e., velocity, acceleration, and acceleration rate, are effectively estimated. In addition, as for a fast-moving target with Doppler ambiguity, two cases, i.e., target azimuth spectrum within a pulse repetition frequency (PRF) and spanning over neighboring PRF bands, are analyzed. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can acquire a close integration performance but with lower computational complexity since the parameter searching dimension is reduced. Simulated processing results are provided to validate the effectiveness of the proposed method. © 1991-2012 IEEE.

关键词： Space-based radar

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On the Ergodic Capacity of Multiple Antenna Cognitive Satellite Terrestrial Networks

On the Ergodic Capacity of Multiple Antenna Cognitive Satell...

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Ad-Hoc and Sensor Networks Symposium

作者： Kang An Min Lin Tao Liang Jian Ouyang Wei-Ping Zhu College of Communications Engineering PLA University of Science and Technology National Mobile Communications Research Laboratory Southeast University Nanjing Institute of Telecommunication Technology Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Department of Electrical and Computer Engineering Concordia University

ISBN: (纸本)9781479966653

The integration of cognitive radio (CR) into satellite networks is recognized as an effective strategy to enhance the efficiency of radio spectrum. This paper investigates the ergodic capacity of a multiple antenna cognitive satellite terrestrial network, where the secondary terrestrial system can coexist with the primary satellite system as long as the interference imposed from the secondary user (SU) to the primary user (PU) is below a predefined threshold. Specifically, the Meijer-G function based analytical expression for the ergodic capacity of the secondary network is derived, which not only provides an efficient means to evaluate the system performance but also characterize the impact of various channel parameters on the network. Finally, simulation results are provided to demonstrate the validity of the theoretical analysis.

关键词： Cognitive satellite terrestrial network Multiple antenna Ergodic capacity

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Throughput-delay tradeoff for wireless multichannel multi-interface random networks

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Canadian Journal of electrical and computer engineering 2015年第2期38卷 162-169页

作者： Ma, Xiaolin Li, Fangmin Liu, Jian Liu, Xinhua Key Laboratory of Fiber Optical Sensing Technology and Information Processing School of Information Engineering Wuhan University of Technology Wuhan430070 China Department of Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ07030 United States

Capturing throughput-delay tradeoff in wireless networks has drawn considerable attention, as it could bring better usage experience by considering different requirements of throughput/delay demands. Traditional works consider only typical single-channel single-interface networks, whereas multichannel multi-interface (MCMI) networks will become mainstream since they provide concurrent transmissions in different channels, which in turn helps each node to obtain better performance. Unlike previous works, this paper investigates the throughput-delay tradeoff for MCMI random networks. Two queuing systems, i.e., the M/M/m queuing system and the m M/M/1 queuing system, are established for MCMI nodes, and a parameter in routing implementation named routing deviation is also considered in the analytical model. This paper studies concurrent transmission capacity (CTC) using the physical interference model and also explores the impact on CTC of different physical parameters. Moreover, the relations between throughput and delay are achieved using two queuing systems in MCMI random networks respectively. The deterministic results obtained with a group of real network configuration parameters demonstrate that the proposed tradeoff model could be applied to the real network scenarios. © 2015 IEEE.

关键词： Queueing networks

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Extended multi-structure local binary pattern for high-resolution image scene classification

Extended multi-structure local binary pattern for high-resol...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaoyong Bian Chen Chen Qian Du Yuxia Sheng Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Department of Electrical Engineering University of Texas at Dallas Richardson TX USA Department of Electrical and Computer Engineering Mississippi State University Mississippi State USA School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

This paper presents a novel extended multi-structure local binary pattern (EMSLBP) approach for high-resolution image classification, generalizing the well-known local binary pattern (LBP) approach. In the proposed EMSLBP approach, three-coupled descriptors with multi-structure sampling are proposed to extract complementary features (pixel value and radial difference) from local image patches. The anisotropic features derived from elliptical sampling are also rotation invariant by averaging the histograms over rotational angles and combined with the isotropic features extracted from circular sampling. Experimental results show that the proposed method can effectively capture local spatial pattern and local contrast, consistently outperforming several state-of-the-art classification algorithms.

关键词： Feature extraction Histograms Nickel Image classification Support vector machines Training Image resolution

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Unsupervised speaker adaptation of deep neural network based on the combination of speaker codes and singular value decomposition for speech recognition 40

Unsupervised speaker adaptation of deep neural network based...

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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Xue, Shaofei Jiang, Hui Dai, Lirong Liu, Qingfeng National Engineering Laboratory of Speech and Language Information Processing University of Science and Technology of China Hefei China Department of Electrical Engineering and Computer Science York University Toronto Canada

ISBN: (纸本)9781467369978

Recently, we have proposed a general adaptation scheme for deep neural network based on discriminant condition codes and applied it to supervised speaker adaptation in speech recognition based on either frame-level cross-entropy or sequence-level maximum mutual information training criterion [1, 2, 3, 4]. In this case, each condition code is associated with one speaker in data, which is thus called speaker code for convenience. Our previous work has shown that speaker code based methods are quite effective in adapting DNNs even when only a very small amount of adaptation data is available. However, we have to use a large speaker code size and complex processes to obtain the best ASR performance since good initializations of speaker codes and connection weights are very important. In this paper, we propose a method using singular value decomposition (SVD) as in [5] to initialize speaker codes and connection weights to obtain a comparable ASR performance as before but with a smaller speaker code size and much less computation complexity. Meanwhile, we have evaluated unsupervised speaker adaptation with the proposed method in large vocabulary speech recognition in the Switchboard task. Experimental results have shown that it is effective for providing well initializations and suitable in adapting large DNN models. © 2015 IEEE.

关键词： Deep Neural Network (DNN) singular value decomposition (SVD) Speaker Adaptation Speaker Code

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Counterattack detection in broadcast soccer videos using camera motion estimation

Counterattack detection in broadcast soccer videos using cam...

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2015 International Symposium on Artificial Intelligence and Signal processing, AISP 2015

作者： Sigari, Mohamad-Hoseyn Soltanian-Zadeh, Hamid Kiani, Vahid Pourreza, Amid-Reza Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Machine Vision Research Laboratory Computer Engineering Department Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781479988174

This paper presents a new method for counterattack detection using estimated camera motion and evaluates some classification methods to detect this event. To this end, video is partitioned to shots and view type of each shot is recognized first. Then, relative pan of the camera during far-view and medium-view shots is estimated. After weighting of pan value of each frame according to the type of shots, the video is partitioned to motion segments. Then, motion segments are refined to achieve better results. Finally, the features extracted from consecutive motion segments are investigated for counterattack detection. We propose two methods for counterattack detection: (1) rule-based (heuristic rules) and (2) SVM-based. Experiments show that the SVM classifier with linear or RBF kernel results in the best results. © 2015 IEEE.

关键词： Motion estimation

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Virtual Frame Aggregation: Clustered Channel Access in Wireless Networks

Virtual Frame Aggregation: Clustered Channel Access in Wirel...

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IEEE International Conference on Communications

作者： Xuan Dong Shaohe Lv Chunsheng Zhu Rukhsana Ruby Xiaodong Wang Xingming Zhou Victor C. M. Leung National Laboratory of Parallel and Distributed Processing National University of Defense Technology Department of Electrical and Computer Engineering The University of British Columbia

ISBN: (纸本)9781467364300

Coordination among users is inevitable in wireless communication for efficient medium access. Even though the data rate of individual user increases significantly, the performance of wireless network does not grow up accordingly due to the high MAC coordination overhead. In this paper, we present VFA, namely virtual frame aggregation, to achieve high coordination efficiency by amortizing the overhead over multiple transmissions. VFA provides a novel way to construct a winner cluster and allow the winners to transmit without interruption. Specifically, in a multicarrier network, every contending node chooses a subcarrier and the nodes are ordered by the index of the chosen subcarrier. When there are some subcarriers chosen by two or more nodes, an additional slot is exploited to reorder the collided nodes. Finally, all ordered nodes form a cluster and the transmissions are issued sequentially and uninterruptedly. Simulation results show that usually two slots are enough to construct a sufficiently large winner cluster. Moreover, VFA achieves a notable throughput gain over IEEE 802.11 as high as 120% with better fairness under various scenarios.

关键词： Wireless communication Antennas Wires

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A Generalized Piecewise Quadratic Lyapunov Function Approach to Estimating the Domain of Attraction of a Saturated System

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IFAC-PapersOnLine 2015年第11 11期48卷 120-125页

作者： Li, Yuanlong Lin, Zongli Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904-4743 United States

This paper revisits the problem of estimating the domain of attraction of a saturated system with an algebraic loop. A piecewise quadratic Lyapunov function of an augmented state vector composing of the system state and the saturated input has been proposed for use in estimating the domain of attraction for a saturated system. Considering the relationship between the system states and the saturation function, we propose in this paper a generalized piecewise quadratic Lyapunov function, which results from adding a term that characterizes the regional sector condition of the saturated input to the piecewise quadratic Lypunov function. The matrix associated with the generalized piecewise quadratic Lyapunov function is not required to be positive definite, and thus a set of less conservative stability conditions are established, from which a larger estimate of the domain of attraction can be obtained. Simulation results indicate that the effectiveness and superiority of the proposed method. © 2015

关键词： Lyapunov functions Domain of attraction Input saturation Piece wise quadratic Lyapunov function Positive definite Saturated systems Saturation function Sector condition Stability condition

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Improving secrecy performance via device-to-device jamming in cellular networks

Improving secrecy performance via device-to-device jamming i...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Jian Ouyang Min Lin Wei-Ping Zhu Kang An Lei Wang Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Nanjing China Nanjing Institute of Telecommunication Technology Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal QC Canada College of Communications Engineering PLA University of Science and Technology Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (纸本)9781509028610

In this paper, we study the secrecy performance of a cellular network, where a device-to-device (D2D) communication shares the spectral resources with a multi-antenna base station (BS). By assuming known the channel state information (CSI) of the legitimate user and using the maximal ratio transmission (MRT) at the BS, we first derive a closed-form expression of the ergodic secrecy capacity (ESC) for the wiretap channel as well as the ergodic capacity (EC) for the D2D link. Then, we present a simple yet efficient power allocation scheme to maximize the secrecy performance while satisfying the D2D transmission requirement. Finally, numerical results are given to demonstrate the merit of our study, concluding that the interference from the D2D communication can be exploited as a friendly jammer to enhance the security transmission in cellular networks.

关键词： Device-to-device communication Cellular networks Antennas Resource management Jamming Security Optimized production technology

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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