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检索条件"主题词=detection algorithms"

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Evaluation of the single and two data set STAP detection algorithms using measured data

Evaluation of the single and two data set STAP detection alg...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Elias Aboutanios Bernard Mulgrew School of Electrical Engineering and Telecommunications University of New South Wales Sydney NSW Australia Institute for Digital Communications University of Edinburgh Edinburgh UK

Traditional space time adaptive processors for radar target detection require a training data set which is usually drawn from adjacent range gates. Clutter heterogeneity, however, can severely limit the available training sample support and consequently degrade the detection performance. The SDS algorithms, on the other hand, overcome this problem by operating solely on the test data without recourse to training data. In this paper we evaluate both of these approaches, in particular the AMF and MLED, using the MCARM data set. We illustrate the performance degradation of the AMF that results from the clutter heterogeneity and the corresponding advantage of the MLED. We also show that a calibration step of the spatial steering vectors results in significant performance improvement of all of the algorithms considered here.

关键词： detection algorithms Training data Testing Radar detection Covariance matrix Clutter Interference Detectors Degradation Filters

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Study on Automated Incident detection algorithms for Freeways Based on SVM

Study on Automated Incident Detection Algorithms for Freeway...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Guiyan Jiang Zhili Cai Longhui Gang Haifeng Guo College of Transportation Jilin University Changchun China

Aimed at the problem that many AID algorithms have lower detection rate and higher false alarming rate, this paper proposed a kind of AID algorithms for freeways based on SVM. The eigenvector reflecting traffic state was designed according to selected traffic measures that can be provided by many kinds of traffic sensors. AID algorithms were designed based on different sorts of SVM models and tested and compared with simulated data. The results showed that the performances of proposed methods are better than selected classic AID algorithms

关键词： detection algorithms Traffic control Support vector machines Transportation Educational institutions Algorithm design and analysis Testing Intelligent control Automation

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Comparison of signal peak detection algorithms for self-gated cardiac cine MRI

Comparison of signal peak detection algorithms for self-gate...

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Computers in Cardiology (CinC)

作者： G.M. Nijm A.V. Sahakian S. Swiryn A.C. Larson Northwestern University Evanston IL USA

Self-gating (SG) is a cardiac MRI technique to synchronize data acquisition to the cardiac cycle based upon MR signal triggers as opposed to conventional ECG triggers. Fourteen healthy subjects underwent cardiac MRI scans in four different orientations: two chamber, three chamber, four chamber, and short axis. SG trigger times were computed using two methods, first difference and template matching, and ECG trigger times were also recorded for comparison. The root-mean-square (RMS) error was used to evaluate performance, defined as the variability relative to the mean difference between SG trigger times and ECG trigger times. The mean RMS error was lower for template matching than first difference approach for all scan orientations; the improvement in RMS error was statistically significant for all orientations except short axis. In conclusion, compared to the first difference approach, template matching improved the accuracy of trigger detection for two, three, and four chamber SG cardiac MRI scans.

关键词： Signal detection detection algorithms Magnetic resonance imaging Electrocardiography Frequency synchronization Interference Data acquisition Signal processing Low pass filters Magnetic switching

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A performance comparison of deadlock prevention and detection algorithms in a distributed file system

A performance comparison of deadlock prevention and detectio...

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International Phoenix Conference on Computers and Communications (IPCCC)

作者： A. Hac X. Jin J.-H. Soo AT&T Bell Labaratories Naperville IL USA Department of Computer Science Johns Hopkins University Baltimore MD USA

A description is given of an implementation and performance evaluation of different deadlock prevention and detection algorithms. The algorithms are implemented in a locally distributed system. A number of experiments were executed in a distributed system for various lengths of file operation and different numbers of files. The performance of the system and of each algorithm is evaluated and discussed.< >

关键词： System recovery detection algorithms File systems Computer science Resource management Process control Computational complexity Polynomials Performance analysis Algorithm design and analysis

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Research on the detection algorithms for the V-BLAST System

Research on the Detection Algorithms for the V-BLAST System

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International Conference on Internet Technology and Applications (iTAP)

作者： Xiao-Hua Ma Zi-Wei Zheng Ting-ting Cao College of Information Science and Engineering Ningbo University Ningbo China

Layered space-time code technique is a good scheme to improve the wireless transmission rate and reliability. The paper discusses four detection algorithms for the Vertical-Bell Laboratories Layered Space-Time (V-BLAST) system. Then, it analyzes the process of algorithms in detail and simulates them. The bit error rate (BER) for the four detection algorithms in different channel situations are compared.

关键词： detection algorithms Binary phase shift keying Bit error rate Antennas Space time codes Wireless communication

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A Neural Network-Based Optimal Nonlinear Fusion of Speech Pitch detection algorithms

A Neural Network-Based Optimal Nonlinear Fusion of Speech Pi...

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International Conference on Knowledge-Based Engineering and Innovation (KBEI)

作者： Ziba Imani Seyed Jahanshah Kabudian Department of Computer Engineering and Information Technology Razi University Kermanshah Iran

Fundamental frequency estimation is one of the most important issues in the field of speech processing. An accurate estimate of the fundamental frequency plays a key role in the field of speech and music analysis. So far, various methods have been proposed in the time- and frequency-domain. However, the main challenge is the strong noises in speech signals. In this paper, to improve the accuracy of fundamental frequency estimation, we propose a method for optimal nonlinear combination of fundamental frequency estimation methods, in noisy signals. In this method, to discriminate voiced frames from unvoiced frames in a better way, the Voiced/Unvoiced (V/U) scores of four pitch detection methods are combined with nonlinear fusion. These methods are: Autocorrelation (AC), Yin, YAAPT and SWIPE. After identifying the Voiced/Unvoiced label of each frame, the fundamental frequency (F 0 ) of the frame is estimated using the SWIPE method. The optimal function for nonlinear combination is determined using Multi-Layer Perceptron (MLP) neural network (NN). To evaluate the proposed method, 10 speech files (5 female and 5 male voices) are selected from the PTDB-TUG standard database and the results are presented in terms of GPE, VDE, PTE and FFE standard error criteria. The results indicate that our proposed method relatively reduced the aforementioned criteria (averaged in various SNRs) by 25.06%, 20.92%, 13.94%, and 25.94% respectively, which demonstrate the effectiveness of the proposed method in comparison to state-of-the-art methods.

关键词： Noise measurement Estimation detection algorithms Frequency estimation Standards Mathematical model Correlation

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Comparison between the Optimal-Ordered SIC Detector in “Low-Complexity SIC detection algorithms for Multiple-Input Multiple-Output Systems” and a Previous SIC detector

Comparison between the Optimal-Ordered SIC Detector in “Low...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Genquan Chen Hufei Zhu Fuqin Deng Yanyang Liang Faculty of Intelligent Manufacturing Wuyi University Jiangmen China

ISBN: (纸本)9781728119496

In the conclusion of the paper “Low-Complexity SIC detection algorithms for Multiple-Input Multiple-Output Systems” published in 2015, it is claimed that the proposed optimal-ordered successive interference cancellation (OSIC) detector mainly uses “fast Givens rotations” and a new method for updating the squared norms of the rows in the inverse Cholesky factor of the error covariance matrix, to achieve the lowest average complexity among the existing OSIC detectors, including a previous one published in 2011 that also utilizes the inverse Cholesky factor and Givens rotations. This paper shows that “fast Givens rotations” proposed by the above-mentioned paper in 2015 and the Givens rotations utilized in the previous detector are similar and then they should both require the same complexity. We also show that the detector proposed in 2015 and the previous detector both take the dominant complexity to compute the initial inverse Cholesky factor and triangularize the permuted inverse Cholesky factor by Givens rotations, and then the dominant complexity is not affected by the method to update the squared norms of the rows in the inverse Cholesky factor. Finally, it is concluded that both the detectors require the same dominant complexity, including the same average complexity when both of them permute the channel matrix in the same way. On the other hand, we revise the incorrect complexities quoted or claimed in the above-mentioned paper published in 2015, to show that the worst-case complexity of the OSIC detector proposed in 2015 is equal to that of the previous OSIC detector.

关键词： Interference cancellation Detectors Complexity theory detection algorithms Covariance matrices MIMO communication

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Efficient detection algorithms for Spatial Multiplexing Systems

Efficient Detection Algorithms for Spatial Multiplexing Syst...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Wenjie Jiang Yusuke Asai Takeshi Onizawa Satoru Aikawa NTT Access Network Service Systems Laboratories NTT Corporation Yokosuka Kanagawa Japan

Recent studies indicate that spatial multiplexing (SM) systems have enormous potential for increasing the capacity of multiple input multiple output (MIMO) channels in rich scattering environments. In this paper, we present two efficient decision feedback equalization (DFE) algorithms for signal detection of SM scheme. The basic idea behind the new proposals is to reduce the complexity by separating the order search and filter generation. Compared with the conventional DFE detectors with optimal and suboptimal ordering rules, the new algorithms are less complex and achieve error performance that closely approximates that of the standard Bell Labs layered space time (BLAST) algorithm

关键词： detection algorithms Samarium Silicon carbide Decision feedback equalizers MIMO Detectors Scattering Filters Land mobile radio Mobile communication

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Evaluation of Anomaly detection algorithms Made Easy with RELOAD

Evaluation of Anomaly Detection Algorithms Made Easy with RE...

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International Symposium on Software Reliability Engineering (ISSRE)

作者： Tommaso Zoppi Andrea Ceccarelli Andrea Bondavalli Department of Mathematics and Informatics University of Florence Florence (IT)

ISBN: (纸本)9781728149837

Anomaly detection aims at identifying patterns in data that do not conform to the expected behavior. Despite anomaly detection has been arising as one of the most powerful techniques to suspect attacks or failures, dedicated support for the experimental evaluation is actually scarce. In fact, existing frameworks are mostly intended for the broad purposes of data mining and machine learning. Intuitive tools tailored for evaluating anomaly detection algorithms for failure and attack detection with an intuitive support to sliding windows are currently missing. This paper presents RELOAD, a flexible and intuitive tool for the Rapid EvaLuation Of Anomaly detection algorithms. RELOAD is able to automatically i) fetch data from an existing data set, ii) identify the most informative features of the data set, iii) run anomaly detection algorithms, including those based on sliding windows, iv) apply multiple strategies to features and decide on anomalies, and v) provide conclusive results following an extensive set of metrics, along with plots of algorithms scores. Finally, RELOAD includes a simple GUI to set up the experiments and examine results. After describing the structure of the tool and detailing inputs and outputs of RELOAD, we exercise RELOAD to analyze an intrusion detection dataset available on a public platform, showing its setup, metric scores and plots.

关键词： data mining graphical user interfaces learning (artificial intelligence) security of data anomaly detection Data Security graphical user interfaces data mining sliding windows algorithms detection algorithms Intuitive Metronidazole

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Is Objective Function the Silver Bullet? A Case Study of Community detection algorithms on Social Networks

Is Objective Function the Silver Bullet? A Case Study of Com...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Yang Yang Yizhou Sun Saurav Pandit Nitesh V. Chawla Jiawei Han Department of Computer Science & Engineering University of Notre Dame Notre Dame IN USA Department of Computer Science University of Illinois Urbana-Champaign Urbana IL USA

Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting ``reasonable'' communities is an even harder problem. Since the first use of k-means algorithm in 1960s, many community detection algorithms have been invented - most of which are developed with specific goals in mind and the idea of detecting ``meaningful'' communities varies widely from one algorithm to another. With the increasing number of community detection algorithms, there has been an advent of a number of evaluation measures and objective functions such as modularity and internal density. In this paper we divide methods of measurements in to two categories, according to whether they rely on ground-truth or not. Our work is aiming to answer whether these general used objective functions are well consistent with the real performance of community detection algorithms across a number of homogeneous and heterogeneous networks. Seven representative algorithms are compared under various performance metrics, and on various real world social networks.

关键词： Communities Social network services detection algorithms Measurement Clustering algorithms Benchmark testing Cities and towns

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