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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Barbara Ripani Andrea Modenini Guido Montorsi Dep. of Elec. and Telecomm. (DET) Politecnico di Torino Torino Italy RF system division European Space Agency Noordwijk The Netherlands

ISBN: (纸本)9781665435413

In this paper, we consider channels affected by Wiener phase noise and derive a detection algorithm that exploits oversampling at the receiver for tracking better the phase noise variations. The resulting algorithm is a multi-sample discrete-phase BCJR that outperforms receivers using a single sample per symbol and maximizes the achievable information rate over phase noise channels. Finally, we assess the suitability of the multi-sample discrete-phase BCJR for performing iterative detection and decoding with standard codes.

关键词： Phase noise Codes Symbols Receivers Iterative methods Global communication detection algorithms

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Adaptation Processes in Asymptotic Safety Management

Adaptation Processes in Asymptotic Safety Management

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Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO)

作者： A. N. Petukhov S. D. Erokhin P. L. Pilyugin Moscow Technical University of Communications and Informatics Moscow Russia

ISBN: (数字)9781665470643

ISBN: (纸本)9781665470650

The functions of the adaptive contour of the asymptotic information security management architecture are determined. The directions of adaptation that provide a fully functional response to security events, a computer attack or an incident are highlighted, the role of a retrospective and reference flow of security events is established, the properties of attack detection algorithms that ensure the adequacy and reliability of adaptation transactions are shown. The use of the concept of "Common criteria" for the asymptotic management of security policies is proposed.

关键词： Safety management Information security Computer architecture Telecommunications Synchronization Reliability detection algorithms

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An Indoor Map Matching Algorithm Based on Improved Particle Filter

An Indoor Map Matching Algorithm Based on Improved Particle ...

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International Conference on Information, Communication and Networks (ICICN)

作者： Baoguo Yu Haonan Jia Xinjian Wang Shuang Li State Key Laboratory of Satellite Navigation System and Equipment Technology The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China College of Instrument Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781665490832

In order to correct the location result of indoor map matching algorithm in inaccessible area, a map matching algorithm based on particle filter multiple weight update is proposed in this paper. The map matrix is built on the raster map to make full use of the map information, and the five weights of map are calculated by the map matrix to improve indoor map matching accuracy. Meanwhile, the modified wall-penetrating detection method is realized by testing the values of map information matrix elements in the circular particle trajectory to reduce the map matching algorithm calculation amount. The accuracy and effectiveness of the proposed algorithm are verified by simulation and field measurement.

关键词： Atmospheric measurements Computational modeling Layout Particle measurements Particle filters Trajectory detection algorithms

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DragStream: An Anomaly And Concept Drift Detector In Univariate Data Streams

DragStream: An Anomaly And Concept Drift Detector In Univari...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Anne Marthe Sophie Ngo Bibinbe Abdoul J. Mahamadou Michael Franklin Mbouopda Engelbert Mephu Nguifo Université Laval FSAA Canada Université Clermont Auvergne CNRS Mines de Saint-Etienne Clermont-Auvergne-INP LIMOS France

Anomaly detection in data streams comes with different technical challenges due to the data nature. The main challenges include storage limitations, the speed of data arrival, and concept drifts. In the literature, methods for mining data streams in order to detect anomalies have been proposed. While some methods focus on tackling a specific issue, other methods handle diverse problems but may have high complexity (time and memory). In the present work, we propose DragStream, a novel subsequence anomaly and concept drift detection algorithm for univariate data streams. DragStream extends the subsequence anomaly detection method for time series data Drag to streaming data. Furthermore, the new method is inspired by the well-known Matrix Profile, Drag, and MILOF which are respectively point and subsequence anomaly detection methods for time series and data streams. We conducted intensive experiments and statistical analysis to evaluate the performance of the proposed approach against existing methods. The results show that our method is competitive in performance while being linear in time and memory complexity. Finally, we provide an open-source implementation of the new method.

关键词： Statistical analysis Conferences Time series analysis Detectors Time measurement Complexity theory detection algorithms

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Dense Attention Pyramid Networks for Multi-Scale Ship detection in SAR Images

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2019年第11期57卷 8983-8997页

作者： Cui, Zongyong Li, Qi Cao, Zongjie Liu, Nengyuan Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Sichuan Peoples R China Univ Elect Sci & Technol China Ctr Informat Geosci Chengdu 611731 Sichuan Peoples R China

Synthetic aperture radar (SAR) is an active microwave imaging sensor with the capability of working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR images have been widely used in civilian and military fields, such as ship detection. The scales of different ships vary in SAR images, especially for small-scale ships, which only occupy few pixels and have lower contrast. Compared with large-scale ships, the current ship detection methods are insensitive to small-scale ships. Therefore, the ship detection methods are facing difficulties with multi-scale ship detection in SAR images. A novel multi-scale ship detection method based on a dense attention pyramid network (DAPN) in SAR images is proposed in this paper. The DAPN adopts a pyramid structure, which densely connects convolutional block attention module (CBAM) to each concatenated feature map from top to bottom of the pyramid network. In this way, abundant features containing resolution and semantic information are extracted for multi-scale ship detection while refining concatenated feature maps to highlight salient features for specific scales by CBAM. Then, the salient features are integrated with global unblurred features to improve accuracy effectively in SAR images. Finally, the fused feature maps are fed to the detection network to obtain the final detection results. Experiments on the data set of SAR ship detection data set (SSDD) including multi-scale ships in various SAR images show that the proposed method can detect multi-scale ships in different scenes of SAR images with extremely high accuracy and outperforms other ship detection methods implemented on SSDD.

关键词： Marine vehicles Feature extraction Radar polarimetry Synthetic aperture radar Radar imaging Semantics detection algorithms Dense attention pyramid network (DAPN) multi-scale feature maps ship detection synthetic aperture radar (SAR)

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Comparison of Two algorithms for Signal detection in Pulsar-based FSR 19

Comparison of Two Algorithms for Signal Detection in Pulsar-...

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19th International Radar Symposium (IRS)

作者： Kabakchiev, H. Behar, V. Garvanov, I. Kabakchieva, D. Kabakchiev, A. Rohling, H. Bentum, M. Fernandes, J. Sofia Univ St Kliment Ohridski Sofia Bulgaria Inst Informat & Commun Technol Sofia Bulgaria Univ Lib Studies & Informat Technol Sofia Bulgaria Univ Natl & World Econ Sofia Bulgaria Air Traff Serv Author BULATSA Technol Sofia Bulgaria Tech Univ Hamburg Hamburg Germany Univ Twente Enschede Netherlands INESC ID Lisbon Portugal

ISBN: (纸本)9783736995451

Two detection algorithms (heuristic and CFAR) for target detection in pulsar FSR are analyzed using the simulation approach. The simulation results are verified by processing of the experimental data obtained by the radio observatory Dwingeloo in the Netherlands. The simulation and experimental results proved that the CFAR detection algorithm is more effective than the heuristic algorithm and can be successfully used in a pulsar FSR system for protection of air space from unwanted air objects.

关键词： Signal to noise ratio detection algorithms Matched filters Electronic mail Receivers Signal detection Object detection

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A Community detection Algorithm for Heterogeneous Information Networks

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IEEE ACCESS 2020年 8卷 195655-195663页

作者： Liu, Dongjiang Li, Leixiao Ma, Zhiqiang Inner Mongolia Univ Technol Coll Data Sci & Applicat Inner Mongolia Autonomous Reg Engn & Technol Res Big Data Based Software Serv Hohhot 010080 Peoples R China

With the fast development of Internet, many fields have accumulated great amount of data. And plenty of them are organized in heterogeneous information network (HIN), so analyzing HIN efficiently is very necessary. Several HIN clustering algorithms have been proposed in recent years. Most of them are based on meta-path. As instances of meta-paths can connect all the target objects directly, while clustering, all these algorithms only focus on the relationship of two target objects that are connected directly by an instance of meta-paths. In this situation, information contained in the relationship of two target objects that are not directly connected by an instance of meta-paths is neglected. These target object pairs may be very helpful for obtaining better clustering result. In order to take these target object pairs into consideration, a structural neighbor searching method is applied into the proposed algorithm. By using this method, all the indirectly connected neighbors of target objects are considered while performing clustering. Moreover, as more than one meta-paths can be found in a heterogeneous information network and each meta-path can impact the clustering result in different degree, a weight value should be assigned to each meta-path. These weight values are used to represent the relative importance of meta-paths. To obtain these weight values, a calculation method is proposed and the algorithm described in this paper tries to calculate weight values by using this method. With weight values of meta-paths and structural neighbors of target objects, all the vectors of target objects can be calculated. Then the hierarchical clustering procedure will be performed based on these vectors.

关键词： Clustering algorithms Social networking (online) Image edge detection Task analysis detection algorithms Sun Medical services Clustering community detection heterogeneous information networks meta-path vectors

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Implementation of algorithms for Point target detection and tracking in Infrared image sequences

Implementation of algorithms for Point target detection and ...

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IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

作者： Ravi Vaishnavi G Unnikrishnan A A Bazil Raj Defence Institute of Advanced Technology Pune India

ISBN: (数字)9781728106304

ISBN: (纸本)9781728106311

This paper primarily focuses on the study and implementation of two target detection algorithms and also on the formulation of a tracking model to track the detected targets. These detection algorithms- one under the category of Detect before track (DBT) approach and other being Track before detect (TBD) are implemented for point target detection in Infrared Search and Track (IRST) systems for airborne targets. Performance of these algorithms is tested on real Infrared image sequences by plotting receiver operating characteristics (ROC) curves under different scenarios. Results are compared by discussing advantages and shortcomings of both approaches in terms of computational complexity and target detection capability. To track the detected targets with linear trajectories, a tracking algorithm based on Kalman filtering is used. This model is applied for targets under different scenarios and simulation results are presented in this paper.

关键词： Target tracking detection algorithms Object detection Kalman filters Discrete wavelet transforms Continuous wavelet transforms

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Sybil detection in Social-Activity Networks: Modeling, algorithms and Evaluations 26

Sybil Detection in Social-Activity Networks: Modeling, Algor...

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26th IEEE International Conference on Network Protocols (INCP)

作者： Zhang, Xiaoying Xie, Hong Lui, John C. S. Chinese Univ Hong Kong CSE Dept Hong Kong Peoples R China

ISBN: (纸本)9781538660430

Detecting fake accounts (sybils) in online social networks (OSNs) is vital to protect OSN operators and their users from various malicious activities. Typical graph-based sybil detection (a mainstream methodology) assumes that sybils can make friends with only a limited (or small) number of honest users. However, recent evidences showed that this assumption does not hold in real-world OSNs, leading to low detection accuracy. To address this challenge, we explore users' activities to assist sybil detection. The intuition is that honest users are much more selective in choosing who to interact with than to befriend with. We first develop the social and activity network (SAN), a two-layer hyper-graph that unifies users' friendships and their activities, to fully utilize users' activities. We also propose a more practical sybil attack model, where sybils can launch both friendship attacks and activity attacks. We then design Sybil_SAN to detect sybils via coupling three random walk-based algorithms on the SAN, and prove the convergence of Sybil_SAN. We develop an efficient iterative algorithm to compute the detection metric for Sybil_SAN, and derive the number of rounds needed to guarantee the convergence. We use "matrix perturbation theory" to bound the detection error when sybils launch many friendship attacks and activity attacks. Extensive experiments on both synthetic and real-world datasets show that Sybil_SAN is highly robust against sybil attacks, and can detect sybils accurately under practical scenarios, where current state-of-art sybil defenses have low accuracy.

关键词： Twitter detection algorithms Image edge detection Facebook Computational modeling Convergence

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Robust algorithms for Random Signal detection in Condition of Aprioristic Uncertainty

Robust Algorithms for Random Signal Detection in Condition o...

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IEEE International Conference on Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)

作者： Igor Prokopenko Kostiantyn Prokopenko Igor Omelchuk Olena Omelchuk National Aviation University Kyiv Ukraine Fundamentals of Physical National Pedagogical Dragomanov University Kyiv Ukraine

The task of random narrowband signal detection on background of uncorrelated Gaussian noise and chaotic puls interference is considered. Three robust detection algorithms are synthesized and they efficiencies and robu... 详细信息

ISBN: (纸本)9781728125930

关键词： Interference Signal processing algorithms detection algorithms Signal detection Harmonic analysis Probability distribution Detectors

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