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检索条件"主题词=Detection algorithms"

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detection and estimation with redundant range differences

Detection and estimation with redundant range differences

引用

IEEE National Conference on Radar

作者： Sayit Korkmaz Circuits and Systems TU Delft Delft Netherlands

In this paper, we explore the use of redundant range differences in signal estimation and detection. Redundant range differences are known to lie in a certain subspace. This information forms our basis of estimation and detection algorithms. In addition to this information, we also use the configuration of the base stations to check the consistency of range difference estimates. In summary we propose the shrunken estimator as an improvement over the least squares estimator for range difference smoothing. Shrunken estimator is known to give less mean square error compared to the least squares estimator. For detection purposes we propose an method that can passively detect the presence of a signal form redundant range differences which is based on matched subspace detectors.

关键词： Base stations Smoothing methods Position measurement Least squares approximation Signal detection Circuits and systems Estimation detection algorithms Mean square error methods Detectors

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A Gene Immune detection Algorithm with Complement Operator on the Basis of Biological Immune Principles

A Gene Immune Detection Algorithm with Complement Operator o...

引用

International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Ya-Jing Zhang Shuan-Hu Wu Institute of Computer Yantai University Yantai Shandong China

In this paper, a gene immune detection algorithm with complement operator in the artificial immune system is proposed. Such problems as gene detection, immune memory and niching strategy in the algorithms are discussed. Application on the area of anomaly detection is considered. Shown by simulation experiments, the algorithm joined vaccine operator and complement operator improves the problem of hole and keeps variety of antibodies. And its detecting time is also decreased obviously.

关键词： Immune system Algorithm design and analysis Detectors detection algorithms Cloning Biology Monitoring

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The Impact of Adaptive Speckle Filtering on Multi-Channel SAR Change detection

The Impact of Adaptive Speckle Filtering on Multi-Channel SA...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jason Fritz V. Chandrasekar Electrical & Computer Engineering Department Colorado State University Fort Collins CO USA

One of the most promising applications of synthetic aperture radar (SAR) imagery is change detection. However, the success of change detection algorithms is highly dependent on the type of change being detected. With the advent of multi-channel SAR systems (multi-frequency and/or polarimetric) new algorithms to improve change detection are being developed to take advantage of the additional information. However, these algorithms are still hindered by the speckle phenomena of radar imaging. Adaptive neighborhood filtering techniques have been shown to be effective to reduce speckle, but the impact on change detection has not been explored. The research presented explores the impact of an adaptive filtering algorithm on the probability of detection for synthesized changes.

关键词： Speckle Adaptive filters Filtering Radar detection detection algorithms Change detection algorithms Testing Synthetic aperture radar Gas detectors Pixel

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Still image copy detection algorithm robust to basic image modifications

Still image copy detection algorithm robust to basic image m...

引用

International Symposium on Electronics in Marine (ELMAR)

作者： Karol Wnukowicz Grzegorz Galinski Ruben Tous Institute of Radioelectronics Warsaw University of Technology Warsaw Poland Computer Architecture Department Universitat Poliltècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781424433643

The paper presents a method for content based still-image replica detection. This method uses a compact image signature which depends on image content and is invariant to many widely used image processing techniques, such as lossy compression, resizing, resampling, color enhancements and simple rotations. The signature is designed to be usable in big image database: it has small size (a few dozen bytes), the extraction is fast and the comparison of image signatures is very fast. More than million of image signatures per second can be compared on a modern PC. Usage of the method within a framework for digital rights infringements detection in the World Wide Web is also discussed.

关键词： detection algorithms Robustness Image processing Image coding Computer architecture Electronic mail Color Image databases Web sites Image retrieval

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Video shot meta-segmentation based on multiple criteria for gradual transition detection

Video shot meta-segmentation based on multiple criteria for ...

引用

International Workshop on Content-Based Multimedia Indexing, CBMI

作者： Efthymia Tsamoura Vasileios Mezaris Ioannis Kompatsiaris Centre for Research and Technology Hellas Thessaloniki Greece

Shot boundaries provide the basis for almost all high-level video content analysis approaches, validating it as one of the major prerequisites for efficient video indexing and retrieval in large video databases. The successful detection of both gradual and abrupt transitions is necessary to this end. In this paper a new gradual transition detection algorithm is proposed, based on novel features exhibiting less sensitivity to local or global motion than previously proposed ones. These features, each of which could serve as a stand-alone transition detection approach, are then combined using a machine learning technique, to result in a meta-segmentation scheme. Besides significantly improved performance, advantage of the proposed scheme is that there is no need for threshold selection, as opposed to what would be the case if any of the proposed features were used by themselves and as is typically the case in the relevant literature. Comparison of the proposed approach with four popular algorithms of the literature reveals the significantly improved performance of it.

关键词： Gunshot detection systems Indexing Content based retrieval Information retrieval Machine learning Histograms Informatics Telematics Spatial databases detection algorithms

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A New QRS detection Algorithm Based on Empirical Mode Decomposition

A New QRS Detection Algorithm Based on Empirical Mode Decomp...

引用

International Conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Hongyan Xing Minsong Huang Sch. of Electron. & Inf. Eng. Nanjing Univ. of Inf. Sci. & Technol. Nanjing

A new QRS complex detection algorithm based on the empirical mode decomposition (EMD) is proposed in this paper. The EMD can first decompose the ECG signal into a series of oscillatory components called intrinsic mode functions (IMFs). Then with the soft- threshold denoising method on the first three IMFs, we construct the detection layer that is suitable for QRS detection. Using the corresponding relationship between the feature points of QRS complex and the modulus maxima of the detection layer, the QRS complex detection is realized. The proposed EMD-based method was validated through experiments on the MIT-BIH arrhythmia database and a QRS detection rate of 99.34% was achieved.

关键词： detection algorithms Electrocardiography Spline Band pass filters Artificial neural networks Signal processing Information science Noise reduction Spatial databases Filter bank

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Data-Driven Fault detection Based on Process Monitoring using Dimension Reduction Techniques

Data-Driven Fault Detection Based on Process Monitoring usin...

引用

IEEE Conference on Aerospace

作者： James Schimert Boeing Company Seattle WA USA

One goal of integrated vehicle health management (IVHM) for commercial airplane customers is to monitor sensor data to anticipate problems before flight deck effects (FDEs) ground the airplane for unplanned maintenance. Airplane subsystems - such as flight and environmental control systems, electrical and hydraulic power - can have a high number of associated parameters. Monitoring sensor data streams individually can be inefficient, and fail to detect problems. A research effort at The Boeing Company is investigating anomaly detection algorithms for multivariate time series of parametric data. The multivariate process monitoring techniques account for correlation between parameters, and therefore alert when relationships between parameters change, as well as when mean levels of individual parameters change. Since many traditional multivariate process monitoring techniques are not suited for the high number of parameters in airplane subsystems, this paper discusses using dimension reduction techniques. One example is principal component analysis (PCA). If the assumptions behind PCA are not met, then monitoring charts based on conventional PCA alone can show false alarms and bad detectability. Independent component analysis (ICA) is a recently developed method in which the goal is to decompose observed data into linear combinations of statistically independent components. ICA can be considered an extension of PCA since it uses PCA as an initial pre-whitening stage. Like projection pursuit density estimation, ICA searches for projections of the data that are most non-Gaussian.

关键词： Fault detection Principal component analysis Airplanes Condition monitoring Independent component analysis Land vehicles Road vehicles Power system management Control systems detection algorithms

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Hierarchical run time deadlock detection in process networks

Hierarchical run time deadlock detection in process networks

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IEEE Workshop on Signal Processing Systems (SIPS)

作者： Bin Jiang Ed Deprettere Bart Kienhuis Leiden Embedded Research Center Leiden University Netherlands

Deadlock detection is a well-studied problem that may be considered solved from a theoretical point of view. However, specific cases may demand for specific solutions. One such specific case is deadlock detection in Kahn Process Networks. The Kahn process network (KPN) is an expressive model of computation that is widely used to model and specify deterministic streaming applications. The processes in the network communicate point-to-point over FIFO channels whose sizes are undecidable in general. As a consequence, deadlock may occur and, therefore, a run-time deadlock detection mechanism is required. This can be organized in a centralized way, a distributed way, and a hierarchical way. Centralized and distributed procedures have been reported in the literature. In this paper, we propose a novel hierarchical approach for KPN deadlock detection at run time. We also give results for the implementation on the IBM Cell processor.

关键词： System recovery Intelligent networks Computational modeling Computer networks Runtime Concurrent computing Channel capacity detection algorithms Hardware Computer architecture

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Density Based Outlier Mining Algorithm with Application to Intrusion detection

Density Based Outlier Mining Algorithm with Application to I...

引用

Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA

作者： Peng Yang Biao Huang Chongqing University of Arts and Sciences Chongqing China

Presently, outlier mining is used for many areas such as telecommunication, finance and intrusion detection. However, finding outliers needs amounts of computation with most traditional algorithms. Thus, we propose a modified density based outlier mining algorithm in this paper. For every object in dataset, our algorithm need not judge whether there are core objects within the epsiv-neighborhood of it. In addition, the module information of data object is introduced in our algorithm and it can avoid large numbers of unnecessary computation to finding all outliers. The algorithm is applied on the intrusion dataset and experimental results show it obtains efficient performance for outlier mining while maintaining stable detection rates.

关键词： Intrusion detection Finance Conferences Computational intelligence Communication industry Computer industry Mining industry Art Telecommunication computing detection algorithms

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A Robust Graph-Based Algorithm for detection and Characterization of Anomalies in Noisy Multivariate Time Series

A Robust Graph-Based Algorithm for Detection and Characteriz...

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Haibin Cheng Pang-Ning Tan Christopher Potter Steven Klooster Michigan State University Lansing MI USA NASA Ames Research Center Moffett Field CA USA California State University CA USA

detection of anomalies in multivariate time series is an important data mining task with potential applications in medical diagnosis, ecosystem modeling, and network traffic monitoring. In this paper, we present a robust graph-based algorithm for detecting anomalies in noisy multivariate time series data. A key feature of the algorithm is the alignment of kernel matrices constructed from the time series. The aligned kernel enables the algorithm to capture the dependence relationship between different time series and to support the discovery of different types of anomalies (including subsequence-based and local anomalies). We have performed extensive experiments to demonstrate the effectiveness of the proposed algorithm. We also present a case study that shows the utility of applying our algorithm to detect ecosystem disturbances in Earth science data.

关键词： Robustness Kernel Ecosystems Vegetation Data mining Geoscience Telecommunication traffic detection algorithms Earth Conferences

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