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检索条件"主题词=Filtering algorithms"

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Dynamic State Estimation of Distribution Network Based on Strong Tracking Adaptive Cubature Kalman Filter

Dynamic State Estimation of Distribution Network Based on St...

引用

International Symposium on Autonomous Systems (ISAS)

作者： Lei Su Liming Wang Daxing Xu Hailun Wang College of Automation Hangzhou Dianzi University Hangzhou China Zhejiang Rixin Electric Co. Ltd Quzhou China School of Electrical and Information Engineering QuZhou University Quzhou China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

Effective state estimation is a prerequisite for ensuring the safe, stable, and economical operation of distribution networks. The traditional cubic Kalman filter (CKF) typically assumes that the variance of system noise is constant and known. In order to handle situations where noise is unknown, the improved Sage Husa noise statistical estimator is introduced to estimate the mean and variance of noise in time-varying systems in real time. However, the load of the distribution network is diverse and the line topology is complex. To keep up with the system state in a timely manner when the system load suddenly changes, a strong tracking filter is embedded into the adaptive CKF. Simulation based on the IEEE33 node distribution system verify the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm has stronger tracking ability for voltage amplitude and voltage phase angle when the system load suddenly changes.

关键词： Adaptive systems filtering Heuristic algorithms Noise Distribution networks Voltage filtering algorithms

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A High Gain Common Ground Inverter without Electrolytic Capacitors

A High Gain Common Ground Inverter without Electrolytic Capa...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Jiangpeng Yang Fanglin Bai Yanni Ming Yang Li Linzhe Li Zeliang Shu School of Electrical Engineering Southwest Jiaotong University Chengdu China

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

For photovoltaic inverters, a voltage gain of more than 10 times, low leakage current, and low input current ripple are three important requirements. However, these functions cannot be met simultaneously by existing inverter solutions. In this paper, a high-gain common-ground inverter is proposed, which structurally eliminates leakage current. A current feedforward scheme is adopted to extract the second harmonic of the DC current, which is then injected into the duty cycle to suppress the DC current ripple. The pulsating power is stored in the intermediate capacitor, thereby eliminating the electrolytic capacitor. Simulation results show that the gain of the converter can reach up to 15.55, and the ripple of the input current is less than 10%.

关键词： Photovoltaic systems Simulation Capacitors Voltage filtering algorithms Harmonic analysis Inverters Leakage currents Feedforward systems Power harmonic filters

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Mitigating Drift in Extraction of Joint Angle Measurements from Inertial Measurement Unit (IMU) Data

Mitigating Drift in Extraction of Joint Angle Measurements f...

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IEEE Region 10 International Conference TENCON

作者： Jascha Ramar A. Castillo Neftali Karl I. De Guzman Jandre M. Jacinto Jomel Miles M. Romero Gabrielle Angelo P. Sales Jazzmine Gale S. Flores Justine B. Duran Elaine Nicole S. Bulseco Reil Vinard Espino Ma. Belinda C. Fidel Angelito A. Silverio Seigfred V. Prado Jehiel D. Santos Consuelo B. Gonzalez-Suarez Ma. Madecheen S. Pangaliman Department of Electronics Engineering Faculty of Engineering University of Santo Tomas Research Center for the Health Sciences University of Santo Tomas

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

Inertial measurement unit (IMU) sensors are widely used in sports science to acquire motion-related data, such as joint angle measurements, and provide valuable insights into the performance of the athletes. These sensors can be used for specific purposes that needs regular calibration to compensate for drift since assessment of muscle stress rely on these devices. However, sensor-based systems may not always provide accurate joint angle measurements. This paper aims to mitigate the drift of the IMU data by pre-processing it with various sensor fusion algorithms: Complementary filter, Kalman filter, and Madgwick filter. The output of the calibrated IMU sensor device was compared with the data collected from the VICON motion capture system to validate its accuracy. Finally, the calibrated IMU sensor output is used to measure the joint angles. As a result, the complementary filter resulted in a better accuracy and reliability performance than the Kalman and Magdwick filter. The Kalman filter obtained a higher reliability and precision due to its lower variability and standard deviation of 37.68. Moreover, it also indicated that the complementary filter often yielded low error values, suggesting better performance as seen in its Root- Mean-Square Error (RMSE) of 9.75. An Analysis of Variance (ANOVA) test was done, indicating that the RMSE accepts the null hypothesis, H0, that there are no significant differences among the means of the metrics.

关键词： Performance evaluation Accuracy Measurement units Inertial navigation filtering algorithms Sensors Reliability Motion measurement Kalman filters Analysis of variance

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Datapath Optimization of Digital Finite Impulse Response (FIR) Filter for Aerospace Applications

Datapath Optimization of Digital Finite Impulse Response (FI...

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Data, Computation and Communication (ICDCC), International Conference on

作者： Mayuresh Madhav Joshi Ankur Beohar Shambhavi Awasthi Prashant GK Pallabi Sarkar School of Electrical and Electronics Engineering VIT Bhopal University Bhopal India School of Mechanical Engineering VIT Bhopal University Bhopal India

ISBN: (数字)9798331532956

ISBN: (纸本)9798331532963

A Finite Impulse Response (FIR) filter is mainly used in Digital Communication Systems for Aerospace applications like navigation and control, autopilots and avionics and satellite imaging onboard spacecraft. This paper depicts an implementation of a digital FIR filter. The filter is designed based one of the novel solutions for the datapath and operational timing optimization technique using Genetic Algorithm (GA). It is a datapath and controller-based design We have verified the reduction in the operational timing after using the datapath designed using the algorithm compared to the datapath without using the algorithm. We have achieved the reduction in the delay by 14 delay units after implementing the datapath with algorithm.

关键词： Space vehicles Satellites Finite impulse response filters Imaging filtering algorithms Satellite navigation systems Delays Optimization Genetic algorithms Aerospace control

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A Poisson Multi-Bernoulli Mixture approach to tracking trains using Distributed Acoustic Sensing

A Poisson Multi-Bernoulli Mixture approach to tracking train...

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International Conference on Information Fusion

作者： Marco Fontana Thomas Hayder William Freilinger Ángel F. García-Fernández Simon Maskell Dept. of Electrical Engineering and Electronics University of Liverpool United Kingdom Sensonic GmbH Schärding Austria ARIES Research Centre Universidad Antonio de Nebrija Madrid Spain

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper presents an extended target tracking method to track trains using Distributed Acoustic Sensing (DAS) data. The problem is approached using a measurement likelihood based on a Set of Points on a Rigid Body (SPRB) model applied to a clustered version of the Poisson Multi-Bernoulli Mixture filter. The method efficiently handles asymmetric noise within the set of measurements returned by each train, and proposes a solution to merged measurements appearing at crossings. We use experimental data obtained from trains to show that the proposed algorithm has lower localisation and false target error, leading to better performance in terms generalized optimal sub-pattern assignment (GOSPA) metric.

关键词： Target tracking Noise Distributed databases Clustering algorithms filtering algorithms Acoustic measurements Acoustics Sensors Noise measurement

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SO-PFH: Semantic Object-based Point Feature Histogram for Global Localization in Parking Lot

SO-PFH: Semantic Object-based Point Feature Histogram for Gl...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Lv, Jixin Meng, Chao Wang, Yue Sun, Jie Xiong, Rong Pu, Shiliang Hangzhou Hikvis Digital Technol Co Ltd Hikvison Res Inst Hangzhou Peoples R China Zhejiang Univ Hangzhou Peoples R China

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Global localization is essential for autonomous mobile systems, especially indoor applications where the GPS signal is denied. Although the appearance-based methods have been successfully applied in various localization tasks, they face various challenges such as light variation, viewpoint changing, and dynamic interference. Additionally, the appearance-based methods usually require a visual feature point map, which increases the storage burden. This paper proposes a novel global localization solution that leverages sparse and repetitive semantic object information. The proposal can fulfill global localization based on object-level maps that are self-built or externally provided. In this solution, the semantic objects are firstly modeled with a point cloud. Then, the object's semantic information is embedded into the geometry of the corresponding point, and the Semantic Object-based Point Feature Histogram (SO-PFH) descriptors of the modeled point clouds are estimated. Finally, the global localization is executed by applying a Geometric Consistency Filter-based RANdom SAmple Consensus (GCF-RANSAC) method to match point clouds. Experiments and simulations are conducted in indoor parking lots. The results demonstrate the effectiveness of the proposed method.

关键词： Location awareness Point cloud compression Matched filters Histograms Visualization Semantics filtering algorithms

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A Hybrid Feature Selection Model for Early Prediction of Metabolic Syndrome

A Hybrid Feature Selection Model for Early Prediction of Met...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： A S Sreepadh P Sheshu R G Reshiha T Vinay Kumar Gurusamy Jeyakumar Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Metabolic Syndrome (MetS) is a medical condition that increases the risk of cardiovascular diseases, stroke, and type 2 diseases. Some of the symptoms of MetS are high blood pressure, elevated blood sugar, excess body fat, and abnormal cholesterol levels. All these symptoms are interconnected, which has made early diagnosis of MetS critical. In current medical strategies, there is no personalized medication which leads to unfavorable health outcomes and further increased risks. This paper aims to address these challenges by identifying optimal feature subsets required for the early prediction of MetS. To get the optimal features a hybrid model is proposed in this paper. The proposed model utilizes both the filter method and the wrapper method. Firstly, features are selected using the correlation coefficient (CC) method which is a filter method, and then the selected features are further refined using genetic algorithm (GA) which is a wrapper method. This hybrid model increases the prediction accuracy and reduces computational cost. The methodology of the proposed model, its experimental setup, the results obtained, and the inferences gained are presented in this paper.

关键词： Correlation coefficient Sentiment analysis Accuracy Computational modeling Predictive models filtering algorithms Stroke (medical condition) Feature extraction Medical diagnostic imaging Genetic algorithms

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Novel Civil Engineering Construction Site Safety Monitoring and Warning System based on Machine Vision

Novel Civil Engineering Construction Site Safety Monitoring ...

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Electronics and Renewable Systems (ICEARS), International Conference on

作者： Qiankun Zhang Qibin Cheng Zhejiang Construction Investment Innovation Technology Co. Ltd. Hangzhou China Zhejiang Construction Engineering Group Co. Ltd. Hangzhou China

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Machine vision is widely used in the engineering field, especially in the intelligent monitoring, safety warning and information recognition scenarios. In this study, the novel civil engineering construction site safety monitoring and warning system based on machine vision is proposed. As a pioneering research, this system realizes all-weather real-time security monitoring by combining the daytime and nighttime image processing technology. In daytime image processing scenarios, this study proposes a new image de-hazing algorithm. This algorithm models the imaging process by improving the atmospheric scattering model. At the same time, the guided filtering algorithm is used for optimization, which significantly improves the image clarity in low-visibility environments. In the night image processing scenario, this study uses infrared imaging technology and filtering algorithms for image enhancement. This operation can effectively solve the challenges of image noise and detail loss in low-light environments. As the core of the model, this study proposes a safety warning framework based on image anomaly detection to meet the special needs of construction sites. This innovative architecture includes human posture rotation detection and image color deviation anomaly recognition. Through such operations, automatic recognition and warning of dangerous behaviors are achieved. Experimental results prove the effectiveness of the recognition algorithm.

关键词： Renewable energy sources Machine vision Atmospheric modeling Scattering Alarm systems filtering algorithms Real-time systems Monitoring Civil engineering Optimization

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Intelligent Intrusion Detection in IoT: Integrating Machine Learning and Feature Automation

Intelligent Intrusion Detection in IoT: Integrating Machine ...

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International Conference on Computer and Automation Engineering, ICCAE

作者： Nazratun Naim Neha A. A. M. Muzahid Md Shamsuzzoha Imrul Jahid Hua Han Yujin Zhang Md Musabbir Hossain Ferdous Sohel School of Electronic and Electric Engineering Shanghai University of Engineering Science Shanghai China Hawaii Natural Energy Institute University of Hawaii at Manoa Honolulu HI USA School of Information Technology Murdoch University Murdoch WA Australia

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

The rapid growth of the internet of things (IoT) raises serious security concerns, demanding effective protection from cyber-attacks. Intrusion detection depends on identifying key features, but despite advances in automation, manual feature selection remains necessary, limiting scalability. To address this limitation, we introduced a hybrid feature selection method that combines filter and wrapper techniques to automatically select important features and enhance the efficiency of machine learning (ML) models for intrusion detection tasks. We utilized the mutual information (MI) algorithm as the filter method and recursive feature elimination (RFE) as the wrapper method. We evaluated the performance of the proposed model on publicly available datasets, HIKARI2021 and UNSW-NB15. We compared the results with several existing methods, and our approach outperformed the state-of-the-art (SOTA) methods in terms of accuracy and training time. We presented comprehensive results, including both quantitative and qualitative analysis, to demonstrate the effectiveness and efficiency of our proposed methods.

关键词： Training Automation Machine learning algorithms Limiting Intrusion detection filtering algorithms Feature extraction Information filters Internet of Things Security

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Optimal Design of LLCL Parameters Based on APSO

Optimal Design of LLCL Parameters Based on APSO

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Zeyuan Huang Youhang Deng Northeast Electric Power University China Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

For the novel LLCL structure, current research primarily focuses on damping strategies. For instance, [4] developed a biquad filter-based active damping method combined with a proportional-integral multiresonant repetitive controller. However, the control strategy must be adjusted accordingly, increasing the complexity of the control algorithm and reducing system reliability and robustness. In contrast, research on LLCL filter parameter design is limited. [5] determined the parameters of each filter component through iterative calculations under various constraints, but this method is complex and often relies on empirical tuning, leading to imprecision.

关键词： Damping Passive filters Design methodology filtering algorithms Robustness Inverters Smart grids Iterative methods Optimization Tuning

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