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检索条件"主题词=detection algorithms"

共 7359 条记录，以下是141-150 订阅

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The effect of channel estimation errors on joint detection algorithms in TD-SCDMA system

The effect of channel estimation errors on joint detection a...

引用

International Conferences on Info-tech and Info-net (ICII)

作者： Shao-li Kang Zheng-ding Qiu Shi-he Li Institute of Information Science Northern Jiaotong University Beijing China China Academy of Telecommunication and Technology Beijing China

We analyze the effect of channel estimation errors on joint detection algorithms in TD-SCDMA system. We quantify how estimation errors affect the SNR in the receiver. We apply this analysis to the zero-forcing block l... 详细信息

ISBN: (纸本)0780370104

关键词： Channel estimation detection algorithms Time division synchronous code division multiple access Computer errors Multiple access interference Algorithm design and analysis Estimation error Synchronous generators Multiaccess communication Intersymbol interference

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Application of Time Series Anomaly detection algorithms in Risk Identification

Application of Time Series Anomaly Detection Algorithms in R...

引用

Computer, Big Data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Dawei Li Jian Zhang Shuai Yang Jian Zhao Bin Zhou Lei Xu Competition Policy and Assessment Center of State Administration for Market Regulation Beijing China

ISBN: (数字)9798331533991

ISBN: (纸本)9798331534004

Traditional risk identification methods often rely on manual inspections and post-event processing, which struggle to cope with the vast amounts of data and the real-time changes in the internet environment. Time series anomaly detection algorithms, as an effective data analysis tool, can identify abnormal changes in time series data. By utilizing spectral residual anomaly detection algorithms and sub-sequence anomaly detection algorithms, models were constructed to conduct an in-depth anomaly detection analysis of price data on the JD platform, providing a new solution for risk identification. The experimental results show that the precision, recall, and F1 scores of these two time series anomaly detection algorithms are significantly better than those of other comparative algorithms, demonstrating significant application value in risk identification.

关键词： Sensitivity Image processing Time series analysis Manuals Inspection Real-time systems Object recognition detection algorithms Anomaly detection Monitoring

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A Review on Community detection algorithms in Social Networks

A Review on Community Detection Algorithms in Social Network...

引用

International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT)

作者： Puneet Kumar Priyanka Chawla Ajay Rana School of Computer Science & Engineering Lovely Professional University Jalandhar Punjab School of Computer Science & Engineering Amity University Noida

ISBN: (数字)9781538677063

ISBN: (纸本)9781538677070

There are many real networks that are closely formed according to a community network. Many researchers have devoted their research efforts to develop algorithms and methods that can efficiently find the hidden pattern in the network which is called community. As there are different kinds of networks having different level of complexity and each may contain different properties, each algorithm in literature holds some of these properties and has different definition of community. As per the definitions provided and algorithms used, only part of the features of real communities gets extracted. Objective of this paper is to find different community detection techniques that are already available, analyze them and find the problem in these algorithms. Objective of paper is to categorize the different community discovery methods on the basis of properties these algorithms contain. The classification is also helpful in further research in community detection.

关键词： Heuristic algorithms Social network services Clustering algorithms detection algorithms Complexity theory Image edge detection Computer science

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The New detection algorithms for Network Traffic Anomalies

The New Detection Algorithms for Network Traffic Anomalies

引用

International Conference on Networking (ICN)

作者： Jun Lv Xing Li Tong Li Acad. of Armoured Forced Eng. Beijing China Education and Research Network Tsinghua University Beijing China Academy of Armored Forces Engineering Beijing China The Academy of Armoured Forced Engineering Beijing China

Network traffic anomaly detection is a difficult problem in network management. This paper presents a wavelet generalized likelihood ratio (WGLR) algorithm and an error performance detection (EPD) algorithm to solve this problem. WGLR algorithm combines generalized likelihood ratio (GLR) algorithm and wavelet transform method, and captures the failure point in real time. Error performance detection (EPD) algorithm is based on the prediction error of the traffic model and regards the error as the statistical variable, comparing with the threshold, which will detect the anomalous change in the signal without test window delay. Simulation and network traffic experiment has demonstrated that the algorithm has better performance in fault detection.

关键词： detection algorithms Telecommunication traffic Traffic control Testing Change detection algorithms Fault detection Wavelet transforms Delay Engineering management Predictive models

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On the Effect and Robustness of Zero-crossing detection algorithms in Simulation of Hybrid Systems Jumping on Surfaces

On the Effect and Robustness of Zero-crossing Detection Algo...

引用

American Control Conference

作者： David A. Copp Ricardo G. Sanfelice Department of Aerospace and Mechanical Engineering University of Arizona 1130 N. Mountain Ave AZ 85721 USA

ISBN: (纸本)9781457710957

Motivated by the fragility to perturbations of hybrid systems jumping on surfaces and the robustifying capabilities of zero-crossing detection algorithms, we propose a hybrid simulator model with incorporated zero-crossing detection. First, we reveal the effect of measurement noise and of discretization to hybrid systems jumping on surfaces. We prove that, under mild regularity conditions, zero-crossing detection algorithms have a robustifying effect on the original system. Then, we argue that, rather than computing the solutions to the discretization of the fragile nominal model, integration schemes with zero-crossing detection actually compute the solutions of a robustified version of the original model. We propose a mathematical model for the hybrid system with incorporated zero-crossing detection as well as a hybrid simulator for it. We show that both the model and simulator are not only robust, but also that the hybrid simulator preserves asymptotic stability properties, semiglobally and practically (on the step size), of the original system. An example illustrates the ideas and results throughout the paper.

关键词： detection algorithms hybrid systems zero crossings Noise measurement simulator Discretization step size Jumping Fragility simulating

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Comparative Analysis of Facial Affect detection algorithms

Comparative Analysis of Facial Affect Detection Algorithms

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Ashin Marin Thomas Myounghoon Jeon Virginia Tech Blacksburg Virginia

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

There has been much research on facial affect detection, but many of them fall short on accurately identifying expressions, due to changes in illumination, occlusion, or noise in uncontrolled environments. Also, not much research has been conducted on implementing the algorithms using multiple datasets, varying the size of dataset and the dimension of each image in the dataset. Our ultimate goal is to develop an optimized algorithm that can be used for real-time affect detection in automated vehicles. To this end, in this study we implemented the facial affect detection algorithms with various datasets and conducted a comparative analysis of performance across the algorithms. The algorithms implemented in the study included a Convolutional Neural Network (CNN) in Tensorflow, FaceNet using Transfer Learning, and Capsule Network. Each of these algorithms was trained using the three datasets (FER2013, CK+, and Ohio) to get the predicted results. The Capsule Network showed the best detection accuracy (99.3%) with the CK+ dataset. Results are discussed with implications and future work.

关键词： Image resolution Lighting Gray-scale Prediction algorithms Real-time systems detection algorithms Vehicles

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Pitch detection algorithms and Voiced/Unvoiced Classification for Noisy Speech

Pitch Detection Algorithms and Voiced/Unvoiced Classificatio...

引用

International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Ekaterina Verteletskaya Kirill Sakhnov Boris Simak Department of Electrical Engineering Czech Technical University Prague Czech Republic

This paper describes pitch tracking techniques, which combine voiced/unvoiced classification and pitch estimation based on cepstral analysis, time autocorrelation, spectro-temporal autocorrelation (STA) and average magnitude difference function (AMDF). Pre- and post processing techniques improving performance of pitch detection algorithms (PDAs) are also presented. PDAs have been evaluated by telephone speech signals, corrupted by additive noise, in order to provide comparison and demonstrate their performance and robustness. Speech signals used for evaluation were taken from the Czech telephone speech database consisted of 5 male and 5 female speakers.

关键词： detection algorithms Speech analysis Autocorrelation Personal digital assistants Telephony Cepstral analysis Speech enhancement Additive noise Noise robustness Databases

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Evaluation of Anomaly detection algorithms Made Easy with RELOAD

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

引用

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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Reduced-complexity detection algorithms for systems using multi-element arrays

Reduced-complexity detection algorithms for systems using mu...

引用

IEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)

作者： X. Li H.C. Huang A. Lozano G.J. Foschini Bell Laboratories Lucent Technologies Inc. Holmdel NJ USA

In BLAST (Bell-Laboratories LAyered Space Time) systems, multiple transmit and receive antennas are employed to achieve very high spectral efficiencies. The ideal detection method for such systems is the maximum-likelihood (ML) algorithm. However, the ML complexity increases exponentially with the number of transmit antennas and the number of bits per modulation symbol. A reduced-complexity detection method has been suggested, using ordered successive interference cancellation. We consider two other suboptimum techniques: channel-based adaptive group detection and multistep reduced-constellation detection. The goal is to reduce the two aforementioned complexity exponentials. The algorithms efficiently combine linear processing with local ML search. We limit the complexity by maintaining small ML searching areas, while maximizing the performance under the complexity constraint by optimizing the front-end linear processing and the selection of the search areas.

关键词： detection algorithms Receiving antennas Fading Maximum likelihood detection Space technology Interference cancellation Signal detection Transmitting antennas Additive white noise Multiuser detection

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Performance evaluation of object detection algorithms

Performance evaluation of object detection algorithms

引用

International Conference on Pattern Recognition

作者： V.Y. Mariano Junghye Min Jin-Hyeong Park R. Kasturi D. Mihalcik Huiping Li D. Doermann T. Drayer Pennsylvania State University University Park PA USA University of Maryland College Park MD USA Department of Defense Fort Meade MD USA

The continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. In this paper a set of seven metrics are proposed for quantifying different aspects of a detection algorithm's performance. The strengths and weaknesses of these metrics are described. They are implemented in the Video Performance Evaluation Resource (ViPER) system and will be used to evaluate algorithms for detecting text, faces, moving people and vehicles. Results for running two previous text-detection algorithms on a common data set are presented.

关键词： Object detection Shape Face detection detection algorithms Vehicles Video sequences Measurement Educational institutions Humans Eyes

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