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检索条件"主题词=detection algorithms"

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MLE-based order statistic automatic CFCAR detection in Weibull background

MLE-based order statistic automatic CFCAR detection in Weibu...

引用

International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Souad Chabbi Toufik Laroussi Mourad Barkat Laboratoire Signaux et Systèmes de Communication Département d'Electronique SISCOM Université de Constantine Constantine Algeria Laboratoire Signaux et Systèmes de Communication SISCOM Département d'Electronique Université de Constantine Constantine Algeria Department of Electrical Engineering American University of Sharjah Sharjah UAE

In this paper, we address the problem of automatic target detection in Weibull clutter and multiple target situations, without any prior knowledge of neither the non stationary clutter statistics in which the radar operates nor the number of outliers that may be present in the reference window. In doing this, we develop the forward and backward order statistic automatic constant false censoring and alarm rates detectors based upon the maximum likelihood estimator, MLE-based F/B-OSACDC-FCAR. The censuring and detection algorithms are a two in one built detector. They select repeatedly a suitable set of ranked cells among all reference cells surrounding the cell under test to estimate the unknown background level and set the adaptive threshold accordingly. The performance of these detectors is evaluated by means of Monte Carlo simulations.

关键词： Statistics Detectors Radar detection Object detection detection algorithms Radar clutter Maximum likelihood detection Maximum likelihood estimation Testing Probability

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Nonparametric spatial analysis for mine line detection

Nonparametric spatial analysis for mine line detection

引用

OCEANS

作者： J. C. Hyland C. M. Smith Naval Surface Warfare Center Panama FL USA

ISBN: (纸本)9781424449606

The development of tools for automated analysis of data collected for mine countermeasures (MCM) search, classify and map (SCM) has predominantly focused on automated target recognition for individual mines. As MCM target detection becomes more automated, detecting spatial patterns in the positioning of mines should follow. Natural restrictions on mine deployment such as depth and bottom contour as well as mine deployment methodology and protocol effectively create mine line patterns that are typical to coastal areas. We have developed a mine line detection algorithm that uses nonparametric spatial analysis to identify mine-like contacts (MLCs) that fit into mine line patterns dictated by standard mine laying protocol in coastal regions. In general, a set of MLCs reported from a mine detection sensor will consist of both actual mines and false alarms; the algorithm classifies every MLC in this set into one of three classes: fixed - the MLC?fits into a mine line pattern with fixed mine spacing; random -the MLC?fits into a mine line pattern with random mine spacing; or false alarm-?-the MLC?does not fit into a mine line pattern and is subsequently not considered a mine. The latest version of the algorithm utilizes nonparametric techniques and requires no knowledge of either the detection sensor's probability of detection (P d ) or probability of false alarm (P fa ). A nonparametric anomaly detector first identifies regions with unusually high MLC density for more detailed analysis. Suspected regions are subsequently analyzed for unusually regular patterns of MLCs. The probabilities that the observed target densities and target patterns could occur simply by chance are estimated by comparison with results from nearby areas using basic information about mine deployment. To ensure that a mine line's full extent is captured, the algorithm attempts to grow a line after it is detected. And a more detailed probability analysis distinguishes random mine lines from fixed-space

关键词： Protocols Sea measurements Pattern analysis Data analysis Data mining Target recognition Object detection detection algorithms Algorithm design and analysis Standards development

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The Research on Collision detection Algorithm Based on Simulated Annealing in Visual Scene Simulation of Missile Attack

The Research on Collision Detection Algorithm Based on Simul...

引用

International Conference on Information Technology and Computer Science, ITCS

作者： Ziying Wang Ping Song Kejie Li Intelligent Robotics Institute School of AeroSpace Science and Engineering Beijing Institute of Technology Beijing China

In this paper, a new collision detection algorithm based on simulated annealing algorithm which is effective in searching optimal solution is presented. Basic principle of this new collision detection algorithm is as follows: The time variant parameter used for establishing objective function based on kinetic equation of missile and attacked objective is extracted firstly; Secondly, objective function adopted as condition of collision detection is constructed availing of extracted parameter; Finally, the optimal solution of objective function is got based on simulated annealing algorithm, and whether the collision happens is determined by the optimal solution. The simulated result proves this new algorithm is feasible.

关键词： detection algorithms Simulated annealing Layout Missiles Kinetic theory Aerospace simulation Computer simulation Computational modeling Intelligent robots Equations

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A Failure detection Model Based on Message Delay Prediction

A Failure Detection Model Based on Message Delay Prediction

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International Conference on Grid and Cooperative Computing (GCC)

作者： Xiaoguang Ding Zhimin Gu Lei Shi Yaosen Hou School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Information Engineering University of Zhengzhou Zhengzhou China

Failure detection is a key technology to implement a high reliable system. It is usually based on overtime mechanism to determine whether a process is failure or not. With the development of network, old failure detectors without adaptive mechanism can not meet the requirements of QoS of application all the time. Adaptive failure detection requires that the failure detectors can dynamically adjust the detecting quality according to the requirements of applications and the variations of network. A new failure detection model based on the predicted message delay is proposed in this paper. An adaptive failure detection algorithm is discussed and realized, which is based on the prediction from historical messages delay time. Experimental results show that the algorithm can satisfy the userpsilas demand of QoS on the failure detector to some extent.

关键词： Predictive models Detectors detection algorithms Quality of service Heart beat Delay effects Object detection Failure analysis Algorithm design and analysis Grid computing

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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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Wavelet and Hilbert transforms based QRS complexes detection algorithm for wearable ECG devices in wireless Body Sensor Networks

Wavelet and Hilbert transforms based QRS complexes detection...

引用

IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Fei Zhang Yong Lian Department of Electrical and Computer Engineering National University of Singapore Singapore

In this paper, an effective approach for QRS detection is presented for wearable ECG devices in wireless Body Sensor Networks (wBSN). Significant reduction of high and low frequency noises are obtained under the action of continuous wavelet transform to original ECG signal after the careful selection of scale level. The following Hilbert transform to the transformed signal enables easier location of R peak points, compared to more difficult zero-crossing point position in conventional wavelet transform methods. The double transformed signal is operated with an improved approximated envelope with the purpose of enhancing the QRS complexes and suppressing the unwanted P/T wave and noises. The performance and reliability of the proposed detector compares very favorably with the published QRS detection approaches.

关键词： Wavelet transforms detection algorithms Electrocardiography Wireless sensor networks Body sensor networks Continuous wavelet transforms Frequency Heart Biomedical monitoring Detectors

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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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A Distributed boundary detection algorithm for multi-robot systems

A Distributed boundary detection algorithm for multi-robot s...

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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： James McLurkin Erik D. Demaine Computer Science Rice University Houston TX USA Electrical Engineering Computer Science MIT CSAIL Cambridge MA USA

We describe a distributed boundary detection algorithm suitable for use on multi-robot systems with dynamic network topologies. We assume that each robot has access to its local network geometry, which is the combination of a robot's network connectivity and the positions of its neighbors measured relative to itself. Our algorithm uses this information to classify robots as boundary or interior in one communications round, which is fast enough for rapidly changing networks. We use the local boundary classifications to create a robust boundary subgraph, and to determine if the boundary is an interior void or the exterior boundary. A proof of the key property of the boundary detection algorithm is provided, and all the algorithms are extensively tested on a swarm of 25-35 robots in rapidly changing network topologies.

关键词： detection algorithms Multirobot systems Robot kinematics Robot sensing systems Computational geometry Distributed algorithms Position measurement Routing Network topology Solid modeling

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An Outlier detection Based DDoS Defense Method

An Outlier Detection Based DDoS Defense Method

引用

IEEE International Symposium on Computer Network and Multimedia Technology, CNMT

作者： Dongqi Wang Yufu Zhu Guiran Chang The Computing Center Northeastern University Shenyang China Comput. Center Northeastern Univ. Shenyang Shenyang China

An outlier detection based large scale distributed denial of service defense method (ODM) is proposed. The ODM method filters suspicious traffic strictly, and establishes a white list at the mean time. Experimental results show that ODM method can be used to defend against larger scale DDoS, and it gives a new way to mitigate collateral damage.

关键词： Law Legal factors Filtering Communication system traffic control Large-scale systems Filters Computer crime detection algorithms Distributed computing Traffic control

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Efficient Outlier detection Algorithm for Heterogeneous Data Streams

Efficient Outlier Detection Algorithm for Heterogeneous Data...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jiadong Ren Qunhui Wu Jia Zhang Changzhen Hu College of Information Science and Engineering Yanshan University슠 Qinhuangdao China School of Computer Science and Technology Beijing Institute of Technology Beijing China

Data streams outlier mining is an important and active research issue in anomaly detection. Most of the existing outlier detection algorithms can only manipulate numeric attributes or categorical attributes. In this paper, we propose an efficient outlier detection algorithm based on heterogeneous data streams, which partitions the stream in chunks. Then each chunk is clustered and the corresponding clustering results are stored in cluster references. The representation degree and the number of adjacent cluster references of each cluster reference are computed to generate the final outlier references, which include potential outliers. Experimental results show that our approach has higher detection precision and better scalability.

关键词： detection algorithms Clustering algorithms Cities and towns Fuzzy systems Educational institutions Information science Data engineering Knowledge engineering Computer science Scalability

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