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检索条件"主题词=Detection algorithms"

共 7324 条记录，以下是41-50 订阅

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Geometric Congestion detection algorithms in the Speed-Flow and Flow-Density Spaces 18

Geometric Congestion Detection Algorithms in the Speed-Flow ...

引用

18th IEEE International Conference on Intelligent Transportation Systems

作者： Moylan, Emily Rey, David Waller, S. Travis Univ New S Wales Sch Civil & Environm Engn Sydney NSW 2052 Australia

ISBN: (纸本)9781467365963

Many ITS applications rely on known attributes of the traffic conditions. One useful property is congestion state which allows for differential behaviour in the system when demand is below, at or above capacity. Congestion detection in certain common data types such as loop detectors is frequently and idiosyncratically addressed by many researchers and practitioners. A set of flexible, objective and robust methods would facilitate the comparison of congestion state across datasets, locations and times of day to better model the response of the system to ITS interventions. This work develops geometric congestion detection algorithms for use in speed-flow and flow-density space. The methods are applicable to any dataset comprised of vehicle flows and speeds (such as loop detector data). The speed-flow space algorithm attempts to identify clusters in speed-flow space based on effective capacity and a cut-off free flow speed. The flow-density diagram builds on the theory supporting the triangular fundamental diagram and classifies congestion based on a density cut-off. Both methods incorporate time-of-day selection. The methods are successful in identifying clearly congested or uncongested observations along a test corridor. In conjunction, the two methods are able to distinguish two regions of ambiguity associated with the transition from uncongested to congested and vice versa. The combination of the two methods offers a promising approach for quickly and robustly classifying observations from a variety of location-typologies into two, three or four traffic states depending on the application.

关键词： intelligent transportation systems road traffic ITS applications flow-density diagram flow-density spaces geometric congestion detection algorithms speed-flow spaces traffic conditions triangular fundamental diagram Approximation algorithms Australia detection algorithms Detectors Mathematical model Monitoring Robustness

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Signal design and detection algorithms for quick detection under false alarm rate constraints 25

Signal design and detection algorithms for quick detection u...

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25th National Conference on Communications (NCC)

作者： Kumar, Alamuru Pavan Vineeth, B. S. UR Rao Satellite Ctr Payload Data Management Grp Bangalore Karnataka India Indian Inst Space Sci & Technol Dept Avion Thiruvananthapuram Kerala India

ISBN: (纸本)9781538692868

In this paper, we consider the design of sequential detection algorithms for the low delay detection of a finite duration transient change signal from noisy observations of the signal under a false alarm rate constraint. Such design problems are motivated by the need to detect explicit control signals with low delay. We propose five heuristic detection algorithms that include algorithms that directly estimate the start time of the signals. In contrast to prior work, we also consider the case where the transient change signal can be apriori designed so as to optimize the detection delay as well as false alarm rate. Using simulations and numerical studies, we compare the average delay and false alarm rate performance of the above algorithms for different choices of the transient change signals.

关键词： Delays Transient analysis detection algorithms Detectors Markov processes Signal design Noise measurement

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Anomaly detection algorithms for the Sleeping Cell detection in LTE Networks 81

Anomaly Detection Algorithms for the Sleeping Cell Detection...

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81st IEEE Vehicular Technology Conference (VTC Spring)

作者： Chernov, Sergey Cochez, Michael Ristaniemi, Tapani Univ Jyvaskyla Dept Math Informat Technol SF-40351 Jyvaskyla Finland

ISBN: (纸本)9781479980888

The Sleeping Cell problem is a particular type of cell degradation in Long-Term Evolution (LTE) networks. In practice such cell outage leads to the lack of network service and sometimes it can be revealed only after multiple user complains by an operator. In this study a cell becomes sleeping because of a Random Access Channel (RACH) failure, which may happen due to software or hardware problems. For the detection of malfunctioning cells, we introduce a data mining based framework. In its core is the analysis of event sequences reported by a User Equipment (UE) to a serving Base Station (BS). The crucial element of the developed framework is an anomaly detection algorithm. We compare performances of distance, centroid distance and probabilistic based methods, using Receiver Operating Characteristic (ROC) and Precision-Recall curves. Moreover, the theoretical comparison of the methods' computational efficiencies is provided. The sleeping cell detection framework is verified by means of a dynamic LTE system simulator, using Minimization of Drive Testing (MDT) functionality. It is shown that the sleeping cell can be pinpointed.

关键词： Sleep Local thermodynamic equilibrium Long Term Evolution detection algorithms Cells anomaly detection data mining

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Compressed Channel Estimation and Data detection algorithms for IR-UWB

Compressed Channel Estimation and Data Detection Algorithms ...

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IEEE International Conference on Ultra-Wideband (ICUWB)

作者： Barbieri, Alessandro Pancaldi, Fabrizio Vitetta, Giorgio M. Univ Modena & Reggio Emilia Dept Informat Engn Reggio Emilia Italy Univ Modena & Reggio Emilia Dept Sci & Methods Engn Reggio Emilia Italy

ISBN: (纸本)9781457717642

In this paper compressed sensing (CS) techniques are employed to develop reduced sampling rate strategies for channel estimation and data detection in impulse radio ultrawideband (IR-UWB) systems. In particular, first channel estimation algorithms based on Matching Pursuit (MP) and Basis Pursuit Denoising (BPDN) techniques are proposed. Then, it is shown how the channel estimates generated by these algorithms can be used in correlation-based CS detectors. Finally, the performance loss originating from CS is assessed analytically in a transmitted reference (TR) system.

关键词： channel estimation data detection detection algorithms CONTAINMENT SPRAY carbon monosulfide Cesium algorithms conditioned stimulus

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Evaluation Method for Arc Fault detection algorithms 40

Evaluation Method for Arc Fault Detection Algorithms

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40th IEEE Photovoltaic Specialists Conference (PVSC)

作者： McConnell, Stephen Wang, Zhan Balog, Robert S. Johnson, Jay Texas A&M Univ College Stn TX 77840 USA Sandia Natl Labs Albuquerque NM 87185 USA

ISBN: (纸本)9781479943982

Many methods have been proposed to detect arc faults within photovoltaic systems. However, because of the dearth of data surrounding arcs that actually occur in commercial or residential PV systems, a sound method is necessary to systematically check for the effectiveness of algorithms claiming the ability to detect PV arc faults. This method should include data representing actual background PV system noise and seek to quantify the limits of the detection capability for the algorithms of interest.

关键词： arc discharges detection algorithms photovoltaic systems

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The Efficiency of detection algorithms for Optimal FTN Signals 19th

The Efficiency of Detection Algorithms for Optimal FTN Signa...

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19th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems (NEW2AN) / 12th Conference on the Internet of Things and Smart Spaces ruSMART (Are You Smart)

作者： Zavjalov, Sergey V. Ovsyannikova, Anna S. Lavrenyuk, Ilya I. Volvenko, Sergey V. Peter Great St Petersburg Polytech Univ St Petersburg Russia

ISBN: (纸本)9783030308599;9783030308582

Optimal signals represent the branch of FTN signaling and may be used for spectral efficiency improvement. Such signals may be detected with a simple coherent bit-by-bit algorithm if the transmission rate is equal to the one defined in the optimization problem. In this case, bit-error rate (BER) performance is close to the theoretical one. Extra increase in symbol rate leads to the necessity of application of more complex detection algorithms. In this paper, different detection algorithm including Viterbi algorithm and maximum likelihood sequence estimations are compared. It is shown that for an 11% increase in the symbol rate algorithm of partial enumeration with 2 iterations may be used instead of the Viterbi algorithm because provides almost the same BER performance with less computational complexity.

关键词： Faster than Nyquist signaling Optimal signals Optimization problem detection algorithms MLSE Viterbi algorithm

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Specification and Evaluation of Geofence Boundary Violation detection algorithms

Specification and Evaluation of Geofence Boundary Violation ...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Stevens, Mia N. Rastgoftar, Hossein Atkins, Ella M. Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781509044948

This paper studies two methods of geofence boundary violation detection. The first method is Ray Casting, which iterates over each geofence boundary edge to determine if a given position of interest is inside the geofence. The second method, called Triangle Weight Characterization (TWC), subdivides the geofence domain into a finite number of triangles, then iterates over each triangle to determine if the given position of interest is inside the geofence. We apply the TWC and Ray Casting methods to case studies that include both keep-in and keep-out geofence boundaries.

关键词： Casting detection algorithms Aircraft Image edge detection Aerospace engineering Algorithm design and analysis Color

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Context Exploitation in Intelligence, Surveillance, and Reconnaissance for detection algorithms 15

Context Exploitation in Intelligence, Surveillance, and Reco...

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IEE* Win* App* Com* Vis* Wor*

作者： Tucker, Jonathan D. Stanfill, S. Robert Lockheed Martin Missiles & Fire Control Appl Res Orlando FL 32819 USA

ISBN: (纸本)9780769554693

Intelligence, Surveillance, and Reconnaissance (ISR) missions involve complex analysis of sensor data that can benefit from the exploitation of geographically aligned context. In this paper we discuss our approach to utilizing geo-registered imagery and context for the purpose of aiding ISR applications. Specifically this includes rendering context masks on imagery, increasing the speed at which detection algorithms process data, providing a way to intelligently control detection density for given ground areas, identifying difficult traffic terrain, and peak suppression refinement.

关键词： feature extraction geophysical image processing image registration rendering (computer graphics) ISR applications ISR missions context exploitation context masks rendering detection algorithms detection density geo-registered imagery geographically aligned context ground areas intelligence-surveillance-reconnaissance missions peak suppression refinement sensor data complex analysis traffic terrain Buildings Context detection algorithms Detectors Process control Rail transportation Rendering (computer graphics) detection algorithms Rail transportation grinding area Process control Reconnaissance image registration Buildings Feature extraction Rendering (computer graphics) Sensor Data

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Performance Effects of Dynamic Graph Data Structures in Community detection algorithms

Performance Effects of Dynamic Graph Data Structures in Comm...

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IEEE High Performance Extreme Computing Conference (HPEC)

作者： Thankachan, Rohit Varkey Swenson, Brian P. Fairbanks, James P. Georgia Inst Technol Sch Comp Sci Atlanta GA 30332 USA Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9781538659892

Community detection algorithms create a dynamic graph as an internal data structure for tracking agglomerative merges. This community (block) graph is modified heavily through operations derived from moving vertices between candidate communities. We study the problem of choosing the optimal graph representation for this data structure and analyze the performance implications theoretically and empirically. These costs are analyzed in the context of Peixoto's Markov Chain Monte Carlo algorithm for stochastic block model inference, but apply to agglomerative hierarchical community detection algorithms more broadly. This cost model allows for evaluating data structures for implementing this algorithm and we identify inherent properties of the algorithm that exclude certain optimizations.

关键词： Data structures detection algorithms Image edge detection Heuristic algorithms Sparse matrices Proposals Partitioning algorithms

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Evaluation of Duplicate detection algorithms: From Quality Measures to Test Data Generation 37

Evaluation of Duplicate Detection Algorithms: From Quality M...

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37th IEEE International Conference on Data Engineering (IEEE ICDE)

作者： Panse, Fabian Naumann, Felix Univ Hamburg Hamburg Germany Univ Potsdam Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9781728191843

Duplicate detection identifies multiple records in a dataset that represent the same real-world object. Many such approaches exist, both in research and in industry. To investigate essential properties of duplicate detection algorithms, such as their result quality or runtime behavior, they must be executed on suitable test data. The quality evaluation requires that these test data are labeled, constituting a ground truth. Correctly labeled, sizable, and real or at least realistic test datasets, however, are not easy to obtain, creating an obstacle for the advancement of research. In this tutorial, we present common methods to evaluate duplicate detection algorithms and to generate labeled test data. We close with a discussion of open problems.

关键词： Industries Runtime Conferences Tutorials Data engineering Object recognition detection algorithms

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