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37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017

作者： Fabrin, Ana C. F. Molin, Ricardo D. Alves, Dimas I. Machado, Renato Bayer, Fabio M. Pettersson, Mats I. Federal University of Santa Maria - UFSM Santa Maria - RS97105-900 Brazil Federal University of PAMPA - UNIPAMPA Alegrete - RS97546-550 Brazil Blekinge Institute of Technology - BTH KarlskronaSE-371 79 Sweden

ISBN: (纸本)9781509049516

This paper presents a study on the constant false alarm rate (CFAR) filter design for change detection algorithms (CDA). More specifically, we are interested in CFAR filters used in CDA for low frequency ultra-wideband (UWB) synthetic aperture radar (SAR) systems. The filter design performance was evaluated in terms of false alarm rate (FAR) and probability of detection (PD). For evaluation purposes, we considered a set of SAR images obtained with the CARABAS-II system. The results are compared with the ones presented in [1], where the same CDA was considered, except for the CFAR filter. The results show that relevant FAR performance improvements can be obtained by just modifying the CFAR filter parameters taking into account the image resolution and target characteristics. © 2017 IEEE.

关键词： Synthetic aperture radar Change detection algorithms detection algorithms Algorithm design and analysis Image resolution

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detection algorithms for physical network coding

Detection algorithms for physical network coding

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International Conference on Communications and Networking in China (CHINACOM)

作者： Chengkang Pan Jianjun Liu Zhenping Hu China Mobile Research Institute Beijing China

This paper investigates multi-user detection (MUD) as well as virtual single-user detection (VSUD) for denoising-based physical network coding in two-way relay channels. In MUD, the two source messages are detected separately and then mapped into a relaying message. In VSUD, the relaying message is obtained directly by detecting the received signal. Maximum likelihood (ML) algorithm and linear algorithms are considered for both single-antenna case and multi-antenna case with and without transmit power and phase control. Suboptimal detection algorithms with lower complexity are also proposed for VSUD. Simulation results show that ML VSUD can achieve better BER performance than ML MUD. The proposed detection algorithms can achieve similar BER performance to ML VSUD .

关键词： detection algorithms Multiuser detection Relays Bit error rate Phase control Network coding Detectors

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detection algorithms and Information Rates for Bit-Patterned Media Storage Systems with Written-in Errors

Detection Algorithms and Information Rates for Bit-Patterned...

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IEEE International Symposium on Information Theory

作者： Jun Hu Tolga M. Duman Erozan M. Kurtas M. Fatih Erden Department of Electrical Engineering Arizona State University Tempe AZ USA Seagate Technologies Inc. Pittsburgh PA USA

ISBN: (纸本)9781424413973;1424413974

This paper studies bit-patterned media recording channels when there exist written-in errors. Using a signal processing point of view, we consider an abstract model for the overall recording channel, incorporating errors occurred during the write process. Based on the resulting channel model, we develop various trellis structures, and propose several detection algorithms for data recovery. Furthermore, we investigate the achievable information rates for patterned media recording systems with different levels of write error probability, which provide an information theoretical performance assessment for such systems.

关键词： detection algorithms Information rates Writing Computer errors Signal processing algorithms Error probability System performance Delay Fabrication Magnetic heads

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detection algorithms for hyperspectral imaging applications: a signal processing perspective

Detection algorithms for hyperspectral imaging applications:...

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IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

作者： D. Manolakis MIT Lincoln Laboratories Lexington MA USA

The purpose of this paper is to present a unified, simplified, and concise, overview of spectral target detection algorithms for hyperspectral imaging applications. We focus on detection algorithms derived using established statistical techniques and whose performance is predictable under reasonable assumptions about hyperspectral imaging data. The emphasis on a signal processing perspective helps to, better understand the strengths and limitations of each algorithm, avoid unrealistic performance expectations, and apply an algorithm properly and sensibly.

关键词： detection algorithms Hyperspectral imaging Signal processing algorithms Object detection Reflectivity Detectors Testing Hyperspectral sensors Sensor phenomena and characterization Electromagnetic measurements

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detection algorithms based on prediction error - additive noise - data orthogonality

Detection algorithms based on prediction error - additive no...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Ibrahim C. Goutis Department of Electrical and Electronic Engineering University of Newcastle UK

Two new iterative algorithms for AR parameter estimation are presented. The first minimizes the sum of the prediction error energy and the cross covariance between prediction error and additive noise, and models the noise covariance matrix with a separate AR filter whose reflection coefficient are constrained to be sufficiently small. The second algorithm minimizes the cross covariance between the prediction error and the data. In both algorithm a steepest descent updating procedure is employed and stability of the AR filter for the stohastic processes is ensured by constraining the corresponding reflection coefficients to be less than one.

关键词： detection algorithms Additive noise Covariance matrix Iterative algorithms Filters Acoustic reflection Predictive models Additive white noise White noise Gaussian noise

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COMPARISON OF ON-LINE CHATTER detection algorithms IN TURNING

COMPARISON OF ON-LINE CHATTER DETECTION ALGORITHMS IN TURNIN...

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International Symposium on Flexible Automation (ISFA)

作者： Vinh Nguyen Melkote, Shreyes Deshamudre, Amar Khanna, Maneesh Walker, Dan Georgia Inst Technol 801 Ferst Dr Atlanta GA 30332 USA Siemens Energy Inc 5101 Westinghouse Blvd Charlotte NC 28273 USA

ISBN: (纸本)9781509034673

Dynamic instability in the form of chatter is a highly undesirable phenomenon that occurs during machining, resulting in poor surface finish and reduced tool life. Though analytical models exist for identifying conditions that avoid chatter, they do not account for process uncertainties or they require extensive cutting tests. Therefore, an on-line chatter detection algorithm is required to detect chatter before irreversible damage to the cutting tool or workpiece occurs. This paper evaluates the performance of three chatter detection algorithms in detecting chatter in the turning process with the eventual goal of developing embedded sensor-based process monitoring automation. Cutting force data are gathered from a number of turning scenarios with varying workpiece geometries. Of the chatter detection algorithms evaluated, spectral analysis is found to be the most robust and capable of detecting dynamic instability before tool or workpiece damage occurs.

关键词： Force Correlation Heuristic algorithms Feeds Turning detection algorithms Dynamics

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Community detection algorithms: A comparative analysis

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Physical Review E 2009年第5期80卷 056117-056117页

作者： Andrea Lancichinetti Santo Fortunato Complex Networks and Systems Institute for Scientific Interchange (ISI) Viale S. Severo 65 10133 Torino Italy Physics Department Politecnico di Torino Corso Duca degli Abruzzi 24 10129 Torino Italy

Uncovering the community structure exhibited by real networks is a crucial step toward an understanding of complex systems that goes beyond the local organization of their constituents. Many algorithms have been proposed so far, but none of them has been subjected to strict tests to evaluate their performance. Most of the sporadic tests performed so far involved small networks with known community structure and/or artificial graphs with a simplified structure, which is very uncommon in real systems. Here we test several methods against a recently introduced class of benchmark graphs, with heterogeneous distributions of degree and community size. The methods are also tested against the benchmark by Girvan and Newman [Proc. Natl. Acad. Sci. U.S.A. 99, 7821 (2002)] and on random graphs. As a result of our analysis, three recent algorithms introduced by Rosvall and Bergstrom [Proc. Natl. Acad. Sci. U.S.A. 104, 7327 (2007); Proc. Natl. Acad. Sci. U.S.A. 105, 1118 (2008)], Blondel et al. [J. Stat. Mech.: Theory Exp. (2008), P10008], and Ronhovde and Nussinov [Phys. Rev. E 80, 016109 (2009)] have an excellent performance, with the additional advantage of low computational complexity, which enables one to analyze large systems.

关键词： Community detection algorithms comparative analysis understanding Community structure community scale complexity classes Complex systems detection algorithms United States BENCHMARKS

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Desgin and comparative study of some sequential jump detection algorithms for digital signals

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1983年第3期31卷 521-535页

作者： M. Basseville A. Benveniste IRISA Rennes France

The purpose of this paper is to analyze the behavior of several jump detection algorithms when applied to the same real data (geophysical signals) and to compare these algorithms from different points of view: complexity, efficiency, robustness, and ability to characterize the detected jumps. Three types of algorithms are investigated: "filtered derivatives" detectors, cumulative sum (cusum) tests, and Willsky's generalized likelihood ratio (GLR) algorithm. A modified version of this last test is elaborated, and a new detector, mixing GLR and cusum tests, is presented.

关键词： detection algorithms Signal processing Robustness Testing Signal analysis Algorithm design and analysis Detectors Speech processing Geology Geologic measurements

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AIDDS: A System for Developing and Testing Incident detection algorithms

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IFAC Proceedings Volumes 1997年第8期30卷 119-124页

作者： John Hourdakis Research Fellow University of Minnesota

Incident management is a major problem in traffic control. Traffic incidents are the cause for more than half of all traffic delays. The research undertaken by the University of Minnesota has reached a point where good knowledge on different incident detection techniques has been achieved. The computer program presented in this paper is designed to assist researchers in testing incident detection algorithms. The primary gains by using this program are the reduction of time needed for algorithm testing and the flexibility on designing the test site. With this program the user can assign individual threshold sets in every section, and use multiple algorithms simultaneously. The algorithms included in the version presented in this paper are DELOS(3,3), CALIFORNIA, Alg. #7, and Alg. #8. Some of the features that make this program unique are its ability to combine measurements on the field to create “pseudo” detectors, its capability to automatically judge if a detection is valid, and its ability to combine incident detection algorithms to improve detection performance.

关键词： detection algorithms Traffic control Computer aided testing Filtering techniques Pattern recognition

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Low-complexity detection algorithms Based on Matrix Partition for Massive MIMO 9

Low-complexity Detection Algorithms Based on Matrix Partitio...

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9th International Conference on Wireless Communication and Signal Processing (WCSP)

作者： Wu, Haijian Lin, Jun Zhang, Chuan Wang, Zhongfeng Nanjing Univ Sch Elect Sci & Engn Nanjing Jiangsu Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538620625

Massive Multiple-Input Multiple-Output (MIMO) is one of the key technologies in the fifth generation (5G) wireless communication for much higher throughput. However, current detection algorithms for massive MIMO suffer from large computational complexity. The Neumann series based approximated matrix inverse is a good tradeoff between detection performance and computational complexity. In this paper, compared to the traditional Neumann series based method, a matrix partition (MP) method is proposed to significantly reduce the number of required multiplications and additions while maintain comparable or even better detection performance. The presented MP method innovates the construction of pre-conditioner matrix and employs the Neumann series method in an intelligent way. Simulation results from a 128 x 16 massive MIMO system with 16-QAM modulation demonstrate that the proposed MP method can reduce the number of multiplications and additions by 68% and 70%, respectively.

关键词： MIMO Computational complexity Uplink Symmetric matrices Signal detection detection algorithms

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