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检索条件"主题词=Detection Algorithms"

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Change detection in Climate Data over the Iberian Peninsula

Change Detection in Climate Data over the Iberian Peninsula

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Raquel Sebastião Pedro Pereira Rodrigues João Gama LIAAD-INESC Porto L.A. & Faculty of Science University of Porta Porto Portugal LIAAD-INESC Porto L.A. & Faculty of Science & Faculty of Medicine University of Porta Porto Portugal

This paper addresses the space-time change detection problem in climate data over the Iberian Peninsula using a 50 years dataset. The data were analyzed concerning the temporal and geographical information, using the following methodology: information about space-time drifts in climate data was obtained by applying a change detection algorithm on all the temporal data available for each physical location considered in this study; the performance and the robustness of this algorithm were then assessed by the McNemar nonparametric statistical test on cluster structures; geographical correlations were inferred using visualization tools and graphical representations of data. Most of the space-temporal drifts detected by the algorithm were confirmed by the results of the McNemar test and are in accordance with visual and graphical representations, supporting the advantage of using inter-disciplinary methods. This analysis also shows that there are locations which do not reveal any change along all the observed years.

关键词： Change detection algorithms Clustering algorithms Testing Data analysis Information analysis Performance analysis Algorithm design and analysis detection algorithms Robustness Data visualization

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VT-AMDF, a pitch detection algorithm

VT-AMDF, a pitch detection algorithm

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Nutthacha Prukkanon Kosin Chamnongthai Yoshikazu Miyanaga Kohji Higuchi King Mongkut's University of Technology Thonburi Bangkok Thailand Hokkaido University Sapporo Hokkaido Japan Department of Electronic Engineering University of Electro-Communications Tokyo Japan

This paper proposes a VT-AMDF pitch detection algorithm which based on average magnitude difference function (AMDF). Time processing is important when implement in real time system. In order to decrease computational time and complexity of pitch detection, the VT-AMDF uses only 55% of total time intervals. The method can reduce the computational time 1.3, 1.4, 4.8 and 5.4 times, compared with original AMDF, autocorrelation function (ACF), normalized square difference function (NSDF) and YIN, respectively. The experiments evaluate on seven words in five different tones of Thai isolated word. The results show that the gross error of VT-AMDF is 3.88%, which is more than original AMDF 0.48 and YIN 0.22, but less than ACF 0.54 and NSDF 1.47.

关键词： detection algorithms Frequency Signal processing algorithms Real time systems Autocorrelation Sampling methods Smoothing methods Paper technology Speech recognition Speech synthesis

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Blind per-state detection of DPSK over correlated fading channels

Blind per-state detection of DPSK over correlated fading cha...

引用

IEEE International Symposium on Information Theory

作者： Alan Barbieri Scuola Superiore Sant'' Anna Pisa Italy

ISBN: (纸本)9781424443123

We consider a differentially encoded phase-shift keying (DPSK) signal transmitted over a channel affected by correlated Rayleigh fading. For this problem, we derive the exact maximum a posteriori (MAP) symbol detection algorithm. By analyzing its properties, we demonstrate that it can be implemented by a forward-backward estimator of the channel, followed by a symbol-by-symbol completion to produce the a posteriori probabilities of the information symbols. The resulting algorithm can be employed as a soft-input soft-output (SISO) block in turbo-iterative receivers and exhibits an excellent performance despite its limited computational complexity. The performance of the proposed algorithm is evaluated for time-domain modulations over frequency-flat channels and for frequency-domain modulations over time-invariant channels.

关键词： Differential quadrature phase shift keying Fading Rayleigh channels detection algorithms Frequency modulation Algorithm design and analysis Iterative algorithms Phase detection Phase shift keying Time domain analysis

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Worm detection in an IPv6 Internet

Worm Detection in an IPv6 Internet

引用

International Conference on Computational Intelligence and Security

作者： Yangui Xu Jiachun Zhou Xiangchun Li Huanyan Qian Sch. of Comput. Sci. & Technol. Nanjing Univ. of Sci. & Technol. Nanjing China Shenyang Artillery Acad. Shenyang China Beijing Comput. Acad. Beijing China

It is a commonly held belief that IPv6 provides greater security against random scanning worms by virtue of a very sparse address space. As a result, worm authors are looking for new ways to acquire vulnerable targets without relying on random scanning for them. It is possible to find vulnerable Web servers by sending carefully crafted queries to search engines or Domain Name System (DNS) queries to DNS servers. In this paper, we discuss scanning strategies of possible worms in the IPv6 Internet. The performance of the worm depends heavily on these strategies, which in turn depend on how secure directory and naming services of a network are. We present an integrated system for the detection and automatic containment of worm propagation in an IPv6 local area network. The detection engine of our system utilizes the DNS anomalies of the worm traffic. We propose a worm detection algorithm based on user habit of sending DNS queries in an IPv6 Internet. Experiment results show that the algorithm is able to detect worms propagation accurately at its early stage in real-time. Our results bring insight on the future battle against worm attacks.

关键词： Internet Computer worms Space technology Domain Name System Local area networks Computer science Telecommunication traffic detection algorithms Web server Search engines

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Impulse UWB energy detection receiver with energy offset synchronization scheme

Impulse UWB energy detection receiver with energy offset syn...

引用

IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Zhuo Zou Yue Ruan Li-Rong Zheng Hannu Tenhunen IPack Vinn Excellence Center School of Information and Communication Technology KTH Royal Institute of Technology Sweden

Impulse ultra-wideband radios (IR-UWB) show strong advantages in low power and low cost applications such as RFIDs and wireless sensor networks. This paper presents an IR-UWB receiver based on energy detection (ED) with on-off keying (OOK) modulation. A novel synchronization and detection algorithm using the energy offset scheme with adaptive threshold detection is suggested, aiming to reduce energy consumption and simplify hardware complexity. Simulation and FPGA implementation reveal that the proposed method can avoid complex and power consuming synchronization blocks, and reduce the preamble length, whereas maintaining the performance in the target level. Hardware integration issues are discussed, implying that the proposed receiver architecture has the possibility to achieve low complexity and low power implementation with several nJs energy per bit, at a data rate of 10 Mb/s.

关键词： Radiofrequency identification Wireless sensor networks Hardware Costs Intelligent sensors Frequency synchronization Energy consumption Radio frequency Ultra wideband technology detection algorithms

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Rough-Based Semi-supervised Outlier detection

Rough-Based Semi-supervised Outlier Detection

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zhenxia Xue Sanyang Liu School of Science Xidian University Xi'an China School of Science Henan University of Science and Technology Luoyang China

With the help of some labeled samples and rough C-means clustering, a rough-based semi-supervised outlier detection (RBSSOD) is proposed, which integrates the advantage of semi-supervised outlier detection (SSOD) and rough C-means clustering. This method takes into account the information of labeled points, as well as the points located in boundary area of each cluster, which can be further discussed the possibility to be reassigned as outliers. Experiment results show that our method not only keep, or improve precision and false alarm rate but also speed up the learning process.

关键词： Clustering algorithms Rough sets Intrusion detection detection algorithms Fuzzy systems Semisupervised learning Partitioning algorithms Computational efficiency Medical diagnosis Unsupervised learning

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Research on ECG R-Wave detection Algorithm Based on LabVIEW

Research on ECG R-Wave Detection Algorithm Based on LabVIEW

引用

International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Danfei Huang Xiaofeng Zhang Huilin Jiang Guozhong Xu School of Life Science and Technology Changchun University of Science and Technology Changchun Jilin China

ISBN: (纸本)9781424441327

This paper introduces a new method of electrocardiogram (ECG) R-wave detection algorithm based on LabVIEW. The algorithm adopts the adaptive difference threshold value method for identifying the R-wave, and calculates the heart rate by the R-R interval. It has the advantages of high detection rate, fast processing, and easy completing and transplanting, therefore the researches lay the foundation for the further research on ECG.

关键词： Electrocardiography detection algorithms Interference Heart rate Object detection Paper technology Wavelet transforms Neural networks Change detection algorithms Data acquisition

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Curved glide-reflection symmetry detection

Curved glide-reflection symmetry detection

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Seungkyu Lee Yanxi Liu Department of Computer Science and Engineering Pennsylvania State University University Park PA USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

We generalize reflection symmetry detection to a curved glide reflection symmetry detection problem. We propose a unifying, local feature based approach for curved glide reflection symmetry detection from real, unsegmented images, where the classic reflection symmetry becomes one of four special cases. Our method detects and groups statistically dominant local reflection axes in a 3D parameter space. A curved glid reflection symmetry axis is estimated by a set of contiguous local straight reflection axes. Experimental results of the proposed algorithm on 40 real world images demonstrate promising performance.

关键词： Reflection detection algorithms Computer vision Image analysis Computer science Object detection Pattern recognition Application software Face detection Vehicle detection

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Research on Credit Card Fraud detection Model Based on Distance Sum

Research on Credit Card Fraud Detection Model Based on Dista...

引用

International Joint Conference on Artificial Intelligence, JCAI

作者： Wen-Fang Yu Na Wang Computer Science and Information Engineering College Zhejiang Gongshang University Hangzhou China

Along with increasing credit cards and growing trade volume in China, credit card fraud rises sharply. How to enhance the detection and prevention of credit card fraud becomes the focus of risk control of banks. This paper proposes a credit card fraud detection model using outlier detection based on distance sum according to the infrequency and unconventionality of fraud in credit card transaction data, applying outlier mining into credit card fraud detection. Experiments show that this model is feasible and accurate in detecting credit card fraud.

关键词： Credit cards Data mining Computer science Educational institutions Artificial intelligence Data analysis Nearest neighbor searches Statistical distributions detection algorithms Database systems

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Context-based endmember detection for hyperspectral imagery

Context-based endmember detection for hyperspectral imagery

引用

Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Alina Zare Paul Gader Department of Computer and Information Science and Engineering University of Florida Gainesville FL USA

An endmember detection algorithm that simultaneously partitions an input data set into distinct contexts, estimates endmembers, number of endmembers, and abundances for each partition is presented. In contrast to previous endmember detection algorithms based on the convex geometry model, this method is capable of describing non-convex sets of hyperspectral pixels. Endmembers are found for non-convex regions by partitioning the set of pixels into convex regions using the Dirichlet process and determining unique endmembers for each region. This novel endmember detection method naturally produces a classifier with a reject class. The algorithm can effectively identify to which context a test data point belongs and identify test pixels for which the associated context is unknown. Results are shown on AVIRIS Indian Pines hyperspectral data. The results show the classification capability of this context-based endmember algorithm.

关键词： Hyperspectral imaging SPICE Partitioning algorithms detection algorithms Geometry Solid modeling Robustness Testing Information science Data engineering

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