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Distributed Variational filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2012年第5期61卷 2305-2318页

作者： Teng, Jing Snoussi, Hichem Richard, Cedric Zhou, Rong N China Elect Power Univ Sch Control & Comp Engn Beijing 102206 Peoples R China Univ Technol Troyes F-10010 Troyes France Univ Nice Sophia Antipolis F-06108 Nice 02 France Chinese Acad Sci Natl Space Sci Ctr Beijing 100190 Peoples R China

The tracking of a moving target in a wireless sensor network (WSN) requires exact knowledge of sensor positions. However, precise information about sensor locations is not always available. Given the observation that a series of measurements are generated in the sensors when the target moves through the network field, we propose an algorithm that exploits these measurements to simultaneously localize the detecting sensors and track the target (SLAT). The main difficulties that are encountered in this problem are the ambiguity of sensor locations, the unrestricted target moving manner, and the extremely constrained resources in WSNs. Therefore, a general state evolution model is employed to describe the dynamical system with neither prior knowledge of the target moving manner nor precise location information of the sensors. The joint posterior distribution of the parameters of interest is updated online by incorporating the incomplete and inaccurate measurements between the target and each of the sensors into a Bayesian filtering framework. A variational approach is adopted in the framework to approximate the filtering distribution, thus minimizing the intercluster communication and the error propagation. By executing the algorithm on a fully distributed cluster scheme, energy and bandwidth consumption in the network are dramatically reduced, compared with a centralized approach. Experiments on an SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy, localization precision, energy consumption, and execution time.

关键词： Bayesian method filtering algorithm simultaneous localization and tracking wireless sensor networks

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Hybrid filtering Optimization Method for Denoising Contaminated Spot Images at Near-Sea-Surface Intervals

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JOURNAL OF COASTAL RESEARCH 2018年第Spe82期000卷 70-76页

作者： Zhu, Wenzhong Wang, Erli Hou, Yani Xian, Lidong Ashraf, Muhammad Aqeel Sichuan Univ Sci & Engn Sch Comp Sci Zigong 643000 Peoples R China Sichuan Vocat Coll Cultural Ind Sch Film & Televis Chengdu 610213 Sichuan Peoples R China Int Water Air & Soil Conservat Soc INWASCON Kuala Lumpur 59200 Malaysia

The presence of noise affects the visual effect of images near the sea surface and reduces the quality of the images. Thus, denoising of the contaminated spot image near the sea surface is required. The current filtering method uses a noise image as mixed model, and uses wavelet transform to denoise a spot image. However, there is a problem of missing details of images near the sea surface. Therefore, a hybrid filtering optimization method of contaminated spot image denoising is proposed. First, the feature extraction of the spot image near the sea surface is carried out, and the contaminated spot image is detected by hybrid filtering. Then the denoising of the contaminated spot image is completed according to the image detection result. Experiments show that the proposed method is practical.

关键词： Image denoising filtering algorithm

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Suboptimal Kalman filtering for linear systems with Gaussian-sum type of noise

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MATHEMATICAL AND COMPUTER MODELLING 1999年第3期29卷 101-125页

作者： Wu, H Chen, G Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA

This paper develops several suboptimal filtering algorithms for discrete-time linear systems that have state and/or measurement noise of the Gaussian-sum type. These new computational schemes are modifications and generalizations of the well-known algorithms of Sorenson and Alspach and of Masreliez. Under the common minimum mean square estimation criterion, these new schemes are derived as recursive computational algorithms. Monte Carte simulations have shown that these new filtering algorithms significantly improve the computational efficiency and/or filtering performance of the existing algorithms. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： filtering algorithm Gaussian sum noise Kalman filter suboptimal filtering

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A graph-based filtering method for top-down mass spectral identification

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BMC GENOMICS 2018年第7期19卷 27-39页

作者： Yang, Runmin Zhu, Daming Shandong Univ Sch Comp Sci & Technol 1500 Shun Hua Lu Jinan 250101 Shandong Peoples R China

Background: Database search has been the main approach for proteoform identification by top-down tandem mass spectrometry. However, when the target proteoform that produced the spectrum contains post-translational modifications (PTMs) and/or mutations, it is quite time consuming to align a query spectrum against all protein sequences without any PTMs and mutations in a large database. Consequently, it is essential to develop efficient and sensitive filtering algorithms for speeding up database search. Results: In this paper, we propose a spectrum graph matching (SGM) based protein sequence filtering method for top-down mass spectral identification. It uses the subspectra of a query spectrum to generate spectrum graphs and searches them against a protein database to report the best candidates. As the sequence tag and gaped tag approaches need the preprocessing step to extract and select tags, the SGM filtering method circumvents this preprocessing step, thus simplifying data processing. We evaluated the filtration efficiency of the SGM filtering method with various parameter settings on an Escherichia coli top-down mass spectrometry data set and compared the performances of the SGM filtering method and two tag-based filtering methods on a data set of MCF-7 cells. Conclusions: Experimental results on the data sets show that the SGM filtering method achieves high sensitivity in protein sequence filtration. When coupled with a spectral alignment algorithm, the SGM filtering method significantly increases the number of identified proteoform spectrum-matches compared with the tag-based methods in top-down mass spectrometry data analysis.

关键词： Mass spectrometry filtering algorithm Spectrum graph

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Partially Observable Multivariate Point Processes with Linear Random Compensators: Analysis and filtering with Applications to Queueing Networks

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IFAC-PapersOnLine 2015年第11 11期48卷 1108-1113页

作者： Borisov, Andrey V. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Russia

The paper is devoted to the optimal filtering problem of the Markov jump state given the multivariate point observations. The investigated observation system is set in terms of the martingale representation. The distinctive feature of the observations is in their compensator, which is a linear random transformation of the unobservable state trajectory. Basing on the predictable martingale characteristics the mutual distribution of the state and observations is reconstructed. The obtained filtering estimate is determined via the finite closed system of the ordinary linear differential equations with a random right-hand side and recursive algebraic relations. The presented theoretical results are applied to the modelling of the service processes in some standard partially observable queueing networks. The paper also contains comparison of the presented filtering algorithm with the classical cases of Kalman-Bucy and Wonham. © 2015

关键词： Queueing theory Kalman filters Linear transformations Markov processes Mathematical transformations Ordinary differential equations Probability distributions Queueing networks Stochastic models Stochastic systems Conditional probability distributions filtering algorithm Markov model Martingale representation Observation systems Optimal filtering Ordinary linear differential equations Stochastic jumps

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Eigenvalue filtering for Random Opportunistic Networks 9

Eigenvalue Filtering for Random Opportunistic Networks

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Zhenhe Li Chao Wang Chao Zhang Xin Yan The Department of Computer Science Wuhan University of Technology

ISBN: (纸本)9781509038237;9781509038220

For the large-scale wireless mobile networks, the topology or global state information directly affects congestion control, traffic control, quality of service and so on. Due to the dynamic change of the opportunistic network structure, the node can not perceive the current state of the network, therefore, it is important to improve the routing quality by designing a topology aware algorithm that can predict the network topology or global state parameters. According to the theoretical deduction and experiment verification of opportunistic network, some conclusions of the average degree and eigenvalue curve is given. Based on these conclusions, an algorithm with multiple measured values for eigenvalue prediction is proposed. The results of the error analysis indicate that the prediction accuracy is obviously improved compared with the traditional Kalman filtering algorithm.

关键词： opportunistic network eigenvalue filtering algorithm multiple measured

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Click-Through Rate Prediction Based on filtering-Enhanced with Multi-head Attention 33rd

Click-Through Rate Prediction Based on Filtering-Enhanced wi...

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33rd International Conference on Artificial Neural Networks and Machine Learning (ICANN)

作者： Yao, Meihan Zhang, Shuxi Lv, Lang Chen, Jianxia Lu, Mengyu Jiang, Gaohang Xiao, Liang Song, Zhina Hubei Univ Technol Sch Comp Sci Wuhan 430068 Peoples R China

ISBN: (纸本)9783031723551;9783031723568

Click-Through Rate (CTR) prediction is a crucial task in recommend systems (RSs), particularly in large-scale industrial applications. CTR models based on graph neural networks (GNNs) is currently the mainstream technology, however, it also encounters challenges in terms of feature interactions and user interests. In the context of RSs, the individual attribute information associated with each entity holds significant importance beyond the inherent interactions between users and items. Rational utilization and capturing of dependencies among these attributes can substantially enhance the predictive accuracy of the model. Therefore, we propose two attention mechanisms of interactions, including internal interaction and external interaction, to handle the information exchange within the attributes of either users or items individually, as well as the interactions between the attributes of users and items. Simultaneously, we introduce a multi-head attention (MHA) mechanism for the interaction selection, to capture features from different dimensions. Furthermore, the behavioral data reflecting user interests unavoidably contains noise, we attenuates noise by utilizing fast Fourier transform (FFT) filtering algorithms to transfer information from the spatial domain to the frequency domain. Experimental results on three benchmarks show that our model outperforms existing SOTA models.

关键词： Click-Through Rate filtering algorithm Graph Neural Networks Feature Interaction

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ACER: Accelerating Complex Event Recognition via Two-Phase filtering under Range Bitmap-Based Indexes 24

ACER: Accelerating Complex Event Recognition via Two-Phase F...

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30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

作者： Liu, Shizhe Dai, Haipeng Song, Shaoxu Li, Meng Dai, Jingsong Gu, Rong Chen, Guihai Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Tsinghua Univ BNRist Beijing Peoples R China

ISBN: (纸本)9798400704901

Complex event recognition (CER) refers to identifying specific patterns composed of several primitive events in event stores. Since full-scanning event stores to identify primitive events holding query constraint conditions will incur costly I/O overhead, a mainstream and practical approach is using index techniques to obtain these events. However, prior index-based approaches suffer from significant I/O and sorting overhead when dealing with high predicate selectivity or long query window (common in real-world applications), which leads to high query latency. To address this issue, we propose ACER, a Range Bitmap-based index, to accelerate CER. Firstly, ACER achieves a low index space overhead by grouping the events with the same type into a cluster and compressing the cluster data, alleviating the I/O overhead of reading indexes. Secondly, ACER builds Range Bitmaps in batch (block) for queried attributes and ensures that the events of each cluster in the index block are chronologically ordered. Then, ACER can always obtain ordered query results for a specific event type through merge operations, avoiding sorting overhead. Most importantly, ACER avoids unnecessary disk access in indexes and events via two-phase filtering based on the window condition, thus alleviating the I/O overhead further. Our experiments on six real-world and synthetic datasets demonstrate that ACER reduces the query latency by up to one order of magnitude compared with SOTA techniques.

关键词： Complex Event Recognition Bitmap Indexes filtering algorithm

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A Multi-Interaction filtering Control Game Model for Close-in Shipborne Gun Weapon System 24

A Multi-Interaction Filtering Control Game Model for Close-i...

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International Conference on Machine Intelligence and Digital Applications (MIDA)

作者： Wu, Hanwen Hou, Yangyang Yang, Luhui Unit 92941 Peoples Liberat Army Huludao Peoples R China Jiangsu Automat Res Inst Lianyungang Peoples R China

ISBN: (纸本)9798400718144

In the realm of future warfare, the inevitable trend towards missile informationization underscores the significance of technological advancements. Within this context, the comprehensive automation of close-in shipborne gun weapon systems holds immense potential to enhance the interception capabilities against anti-ship missiles. This paper delves into the development trajectory of cutting-edge missile technology systems, emphasizing the integration of multi-source data fusion sensing, mobile surprise control, and collaborative game decision-making. Consequently, it identifies the urgent need for the development of autonomous control and interception capabilities within close-in shipborne gun weapon systems. Furthermore, a Multi-Interaction filtering control game model for close-in shipborne gun weapon systems is proposed. This model encompasses adaptive interactive multi-model filtering, enabling it to adapt to a diverse range of target maneuvers. It also incorporates smoother and more precise naval gun follower control, multi-target interception game decision-making, and autonomous collaborative decision-making among formation weapons. This comprehensive approach not only offers a research framework for the development of close-in shipborne gun weapon systems but also serves as a foundation for the simulation and testing platforms of the future.

关键词： Multi-source Data Fusion Interactive Multi-Model Game Theory filtering algorithm

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A Comparison of filtering Techniques on Denoising Terahertz Coaxial Digital Holography Image

A Comparison of Filtering Techniques on Denoising Terahertz ...

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International Symposium on Infrared Technology and Application / International Symposium on Robot Sensing and Advanced Control

作者： Cui, Shan-shan Li, Qi Harbin Inst Technol Natl Key Lab Sci & Technol Tunable Laser POB 30312 YiKuang St Harbin 150080 Peoples R China

ISBN: (纸本)9781510607729;9781510607736

In the process of recording terahertz digital hologram, the hologram is easy to be contaminated by speckle noise, which leads to lower resolution in imaging system and affects the reconstruction results seriously. Thus, the study of filtering algorithms applicable for de-speckling terahertz digital holography image has important practical values. In this paper, non-local means filtering and guided bilateral filtering were brought to process the real image reconstructed from continuous-wave terahertz coaxial digital hologram. For comparison, median filtering, bilateral filtering and robust bilateral filtering were introduced as conventional methods to denoise the real image. Then all the denoising results were evaluated. The comparison indicates that the guided bilateral filter manifests the optimal denoising effect for the terahertz digital holography image, both significantly suppressing speckle noise, and effectively preserving the useful information on the reconstructed image.

关键词： Terahertz imaging digital holography image denoising filtering algorithm

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