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检索条件"主题词=Filtering algorithms"

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OrbitSI: An Orbit-based Algorithm for the Subgraph Isomorphism Search Problem

OrbitSI: An Orbit-based Algorithm for the Subgraph Isomorphi...

引用

IEEE International Conference on Big Knowledge (ICBK)

作者： Syed Ibtisam Tauhidi Arindam Karmakar Thai Son Mai Hans Vandierendonck Queen’s University Belfast Northern Ireland UK Tezpur University Assam India

ISBN: (数字)9798331508821

ISBN: (纸本)9798331508838

The Subgraph Isomorphism (SI) search problem searches for embeddings of a pattern graph within a data graph. Efficient heuristic algorithms for the SI search problem are often structured around a Depth-First Search (DFS) tree-based search to find matching subgraphs. These algorithms comprise three segments: filtering, ordering and enumeration. filtering and ordering are critical in reducing the runtime of the enumeration segment. As such, various properties of vertices are used to filter out impossible matches and determine the most efficient enumeration order. In this paper, we propose using the graphs’ local topological information to strengthen the filtering and ordering segments of a heuristic algorithm, going beyond the properties of vertices and their immediate neighbours, which make up the state-of-the-art strategies. We use orbit counts of 4-vertex graphlets to characterise the local topology near a vertex, which provides valuable structural information while keeping the computational effort for analysing the topology affordable. Our new algorithm, OrbitSI, improves the overall runtime across eight datasets, each containing one data graph and 1800 pattern graphs, by factors of 2.69 to 11.49 compared to four state-of-the-art algorithms.

关键词： Matched filters Backtracking Runtime Heuristic algorithms Knowledge graphs filtering algorithms Search problems Information filters Orbits Topology

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Dynamic Wavelet Filter Design for Denoising Partial Discharge Signal from Insulated Power Cables

Dynamic Wavelet Filter Design for Denoising Partial Discharg...

引用

International Conference on Condition Monitoring and Diagnosis, CMD

作者： Faisal Peer Mohamed Siew Wha Hoon Branislav Vuksanovic Ahmad Ayub Shekhar Mahmud Systems Engineering Department Military Technological College Sultanate of Oman Department of EEE University of Strathclyde Glasgow United Kingdom

ISBN: (数字)9788986510225

ISBN: (纸本)9798350353877

Due to the partial breakdown of insulation present in insulated power cable resulting from ageing, fast rising pulses are injected into cable core conductor and earth screen. Due to noise profile of substation resulted from conducted and radiated emissions, it is often challenging to interpret partial discharge events since classical digital filtering will not be efficient to extract such a wide band frequency partial discharge event. Multi resolution analysis using wavelet filter banks is widely used to extract partial discharge events when hampered by various noise sources. However, the success rate of multi-resolution analysis using wavelet filters relies on degree of correlation between the impulse response of wavelet filter and the discharge pulse itself. There is a clear requirement to have a filter bank having impulse response aligned with propagation characteristics of cables. This paper proposes novel algorithm in designing wavelet basis function using the measured impulse response of the cable under test. Impulse response of cable required to characterize insulated power cable is done by injecting current pulse into cable screen using high frequency current transformer with data acquisition systems. Analysis and synthesis filters perfect reconstruction filter banks are constructed using measured impulse response.

关键词： Partial discharges Partial discharge measurement Wavelet transforms Power cables Current measurement Filter banks filtering algorithms Cable insulation Wavelet analysis Digital filters

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Capacity Degradation Estimation of Lithium Battery Based on Intelligent Particle Filter

Capacity Degradation Estimation of Lithium Battery Based on ...

引用

International Symposium on Autonomous Systems (ISAS)

作者： Xinyu Zhang Xiaoxi Li Miao Gao Yingmin Yi Ni Zhang School of Automation and Information Engineering Xi'an University of Technology Xi'an China The Department of Automation Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

With the booming development of the UAV industry, lithium-ion batteries are gradually being commonly used. For lithium-ion batteries, accurately estimating their battery life degradation can calculate the remaining useful life (RUL) of lithium-ion batteries. Thereby, improving the reliability of lithium-ion battery-driven products and effectively reducing internal and external failure risks. As the current electric charge status of lithium-ion batteries cannot be directly obtained, their capacity degradation model has strong nonlinearity and non-Gaussian characteristics. In order to enhance the accuracy of capacity degradation estimation for lithium-ion batteries, this paper analyses and models the capacity degradation process of lithium-ion batteries using an improved intelligent MH particle filtering algorithm, and compares the estimation results of the proposed new method (MHPF) with those of classical PF and AGPF. The results prove that MHPF can obtain more reliable capacity degradation estimation results for lithium-ion batteries.

关键词： Lithium-ion batteries Degradation Industries filtering Noise Estimation filtering algorithms

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Deep Learning-Based Method for Detecting Surface Defects in Air Filters

Deep Learning-Based Method for Detecting Surface Defects in ...

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Computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Ying Yuan Yajun Lin Tianliang Zhang University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

To prevent defective air filters from reaching the market, it is essential to conduct defect inspections on their appearance. This paper proposes a deep learning-based method for detecting surface defects in air filters. We utilize a linear array camera to capture images of air filters, constructing a dataset and designing a defect detection algorithm. For the outer metal mesh and inner filter material, we propose a multistage detection approach: (1) segmenting the inner and outer structures using a style transfer model; (2) performing defect-free reconstruction of the metal mesh and localizing defects through residual analysis; (3) classifying and pixel-level localizing defects in the connected regions of the filter material. Experimental results demonstrate that the proposed method effectively achieves pixel-level defect localization even in the presence of an imbalance between defective and non-defective data.

关键词： Air cleaners Learning systems Location awareness Surface reconstruction Semantic segmentation Metals Inspection filtering algorithms Image reconstruction Defect detection

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Enhancing Change Detection Robustness: A Whitening Transformation Approach

Enhancing Change Detection Robustness: A Whitening Transform...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fei Liang Qi Zang Zhengyao Wang Yang Hu Dou Quan Shuang Wang School of Artificial Intelligence Xidian University Shaanxi China Aerial Photography and Remote Sensing Group Co. Ltd. Xi’an China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The vast amount of remote sensing data has been instrumental in supporting research on change detection algorithms based on deep ***, factors such as geographical changes and variations in sensor parameters can result in significant style differences between remote sensing images at different time points, leading to a decline in model *** address this issue, this paper proposes a change detection algorithm based on whitening feature extraction, aiming to alleviate distribution differences by decoupling domain-invariant discriminative features from domain-specific style *** effectiveness of the proposed method is demonstrated through transfer experiments from the SVCD dataset to the SZADA dataset and from the SYSU dataset to the SZADA dataset.

关键词： Instruments filtering algorithms Feature extraction Information filters Robustness Data models Sensors

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Adaptive Estimation of Multiple Fading Factors Based on RGAM Model

Adaptive Estimation of Multiple Fading Factors Based on RGAM...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Hongfu Xu Haiyong Luo Zijian Wu Fang Zhao Changhai Lin School of Computer Science Beijing University of Posts and Telecommunications Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China Yibin Tinno Communication Co. Ltd Yibin China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

When there exists a mismatch between the system model or inaccuracies in the statistical characteristics of the noise, it can directly impact the accuracy of current state estimation and potentially lead to filter divergence. In the domain of dynamic positioning and navigation, the Kalman filter has been proposed as a solution to address these issues by incorporating fading factors. Unlike conventional methods for estimating fading factors, this study introduces the RGAM (Resnet Global Attention Mechanism) algorithm model to estimate multiple fading factors associated with state prediction covariance. The RGAM algorithm model leverages the robust estimation capability of network models to accurately estimate the fading factors corresponding to relevant epochs. To validate the effectiveness of the proposed algorithm, experiments were conducted using an actual road data set within the context of a GNSS/INS (Global Navigation Satellite System/ Internal Navigation System) integrated system. Through these experiments, it was observed that employing a filter with accurate fading factors facilitates the avoidance of filter divergence and achieves stable filtering performance in the integrated system.

关键词： Fading channels Adaptation models Accuracy filtering Roads Predictive models filtering algorithms

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Perceptual Encoding Optimization Algorithm Guided by Human Eye Focusing Mechanism

Perceptual Encoding Optimization Algorithm Guided by Human E...

引用

International Conference on Cybernetics, Robotics and Control (CRC)

作者： Xinran Wan Huiping Deng Sen Xiang School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798331517489

ISBN: (纸本)9798331517496

Perceptual coding algorithms play a crucial role in eliminating visual redundancy in video compression. Despite their promising results, there remains potential for further optimization, particularly in leveraging human visual characteristics for rate control and effectively applying just noticeable distortion (JND)a threshold defining human visual sensitivity to changes. In this paper, we propose a novel HEVC rate control scheme inspired by the focusing mechanism of the human visual system (HVS). By integrating saliency and focal distance information, we construct a focusing factor and incorporate it into the encoding framework. This focusing factor serves as a key parameter for rate control, optimizing LCU-level bit allocation and enhancing video coding efficiency. Furthermore, we combine the focusing factor with a JND-based model to design a Gaussian filter that smooths nonfocused areas, reducing background redundancy while enhancing visual quality. The proposed algorithm is implemented on HM16.7, and experimental results show bitrate savings and PSNR improvements ranging from 0.1 to 0.5 dB compared to state-of-the-art algorithms. Additionally, subjective evaluations confirm significantly enhanced visual quality at equivalent bitrates.

关键词： Video coding Visualization Bit rate Redundancy Focusing filtering algorithms Visual systems Distortion Encoding Optimization

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Comparison of TDoA Algorithm Dimension and Modified Kalman Filter for Ultra-wide Band Indoor Positioning System

Comparison of TDoA Algorithm Dimension and Modified Kalman F...

引用

International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Dhonan Nabil Hibatullah Azkario Rizky Pratama Ahmad Ataka Awwalur Rizqi Dept. Electrical & Information Eng. Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350375817

ISBN: (纸本)9798350375824

The Ultra-wideband indoor positioning system (UWB IPS) is a position tracking system that utilizes UWB transceivers. This research explores one of the commonly used techniques in UWB IPS, known as time difference of arrival (TDoA), and addresses two key issues related to TDoA-based UWB IPS: the selection of the TDoA algorithm dimension and filter design, specifically the Kalman filter (KF). This paper presents two distinct experiments to investigate these aspects. The first experiment compares two TDoA algorithms—the Chan algorithm and the Newton-Raphson algorithm—across both two-dimensional and three-dimensional settings. The second experiment evaluates the performance of a modified Kalman filter (KF) for TDoA-based UWB IPS, comparing it with the conventional, unmodified KF. The results from the first experiment indicate that the three-dimensional TDoA algorithm is better suited for indoor applications where tags and anchors are not always at the same level. Conversely, the two-dimensional algorithm performs better when the tag is level with the anchors. In the second experiment, the result shows that the modified KF outperforms the conventional KF, exhibiting adaptive behavior, reduced overshoot during sudden changes in movement, and improved convergence to the reference.

关键词： Fading channels Uncertainty Time difference of arrival filtering algorithms Information filters Transceivers Kalman filters IP networks Indoor positioning systems Ultra wideband technology

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Enhanced Quadratic Extended Kalman Filter

Enhanced Quadratic Extended Kalman Filter

引用

IEEE Conference on Decision and Control

作者： Giovanni Palombo Massimiliano d’Angelo Federico Papa Valerio Cusimano Alessandro Borri Italian National Research Council (IASI-CNR) Istituto di Analisi dei Sistemi e Informatica Rome Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this note, we present a new solution to the filtering problem for stochastic discrete-time nonlinear systems, which we refer to as the Enhanced Quadratic Extended Kalman Filter (eQEKF). Starting from the concept underlying the existing formulation of the Quadratic Extended Kalman Filter (QEKF), based on the definition of an augmented output through Kronecker powers, we propose a different method that enables us to overcome certain inevitable standard approximation issues, reducing the computational workload. Also, we show the effectiveness of the proposed approach with respect to the QEKF and with respect to the classical Extended Kalman Filter, as highlighted by two numerical examples, in the case of Gaussian and non-Gaussian noises.

关键词： filtering Noise Buildings Stochastic processes filtering algorithms Polynomials Trajectory Kalman filters Nonlinear systems Standards

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Feature Selection using Modified PSO with Mutual Information for Tomato Leaf Disease Identification

Feature Selection using Modified PSO with Mutual Information...

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Communication, Control and Intelligent Systems (CCIS)

作者： Chetan Singh Negi H. L. Mandoria Sunita Jalal Krishna Kumar College of Technology GBPUAT Pantnagar India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

Automated disease detection in agriculture is one of the primary focus areas of researchers recently. The captured images are used as input to diagnose the diseases in plants. However, during automated diagnosis, the large number of features with respect to each image is one of the major challenges. The optimal feature selection techniques applied to these input images are often stuck into the local optimum. These features often share a large amount of mutual information, which can be used to reduce the dimensionality of feature set at the primary level before applying any standard feature selection approach. In this work, we have exploited the mutual information to reduce the size of feature set and then applied one of the most popular optimization techniques, PSO, to obtain the optimal feature set. We have compared the results with the optimal features in the absence of any prior reduction in the dimensionality of the feature set.

关键词： Accuracy filtering algorithms Feature extraction Information filters Real-time systems Computational complexity Mutual information Standards Optimization Diseases

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