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检索条件"主题词=Filtering algorithms"

共 10342 条记录，以下是501-510 订阅

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Gaussian Mixture-Based Point Mass filtering

Gaussian Mixture-Based Point Mass Filtering

引用

International Conference on Information Fusion

作者： Felipe Giraldo-Grueso Andrey A. Popov Renato Zanetti Dept. of Aerospace Engineering and Engineering Mechanics The University of Texas at Austin Austin TX USA Oden Institute for Computational Engineering and Sciences The University of Texas at Austin Austin TX USA

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

The accuracy of the point mass filter (PMF) relies on the precise placement of grid points. Since the approximated probability distributions are evaluated only at these points, suboptimal choices in grid placement can result in an inaccurate representation of the posterior distribution. This work addresses this issue by representing the propagated grid points as a Gaussian mixture, enabling a Gaussian sum filter (GSF) update before grid construction. The use of the GSF update enhances the accuracy of the mean and covariance estimates, from which a new grid can be constructed. This approach leads to improved grid placement and reduces the number of points required to achieve satisfactory results. A comparative analysis is conducted between this new approach, the traditional PMF, and a PMF variant that uses an unscented Kalman filter update before grid construction. Using a simple bivariate example, the new variant is shown to approximate the posterior distribution better than the other filters. Furthermore, the new approach is evaluated in two sequential filtering problems: the first involves the Ikeda map, and the second focuses on terrain-relative navigation for Martian exploration. The results show a more accurate, and more consistent filter compared to the other two PMF variants considered.

关键词： Accuracy Navigation filtering algorithms Prediction algorithms Information filters Approximation algorithms Probability distribution Kalman filters Kernel Standards

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Kernel Adaptive filtering with Weibull M-transform Maximum Versoria Criterion

Kernel Adaptive Filtering with Weibull M-transform Maximum V...

引用

IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Chenchong Bi Yingsong Li Liping Li Nikola Zlatanov Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Innopolis Russia

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

A kernel Weibull M-transform maximum-versoria-criterion (KWMMVC) algorithm is constructed, which is to use for nonlinear system identification. The KWMMVC algorithm ingeniously integrates the Weibull M-transform scheme into the maximum-versoria-criterion to formulate a novel cost function. The ability of KWMMVC algorithm to identify nonlinear channels under various impulse noise environments is tested in the kernel adaptive filters, and the results proved its superior performance.

关键词： Adaptive systems Noise Adaptive filters filtering algorithms Information filters Cost function Information and communication technology

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Improving Process Discovery Results by filtering Out Outliers from Event Logs with Hidden Markov Models 23

Improving Process Discovery Results by Filtering Out Outlier...

引用

IEEE 23rd Conference on Business Informatics (CBI)

作者： Zhang, Zhenyu Hildebrant, Ryan Asgarinejad, Fatemeh Venkatasubramanian, Nalini Ren, Shangping San Diego State Univ Dept Comp Sci San Diego CA 92182 USA Univ Calif Irvine Dept Comp Sci Irvine CA 92697 USA

ISBN: (纸本)9781665420693

Process Mining is a technique for extracting process models from event logs. Event logs contain abundant explicit information related to events, such as the timestamp and the actions that trigger the event. Much of the existing process mining research has focused on discovering the process models behind these event logs. However, Process Mining relies on the assumption that these event logs contain accurate representations of an ideal set of processes. These ideal sets of processes imply that the information contained within the log represents what is really happening in a given environment. However, many of these event logs might contain noisy, infrequent, missing, or false process information that are generally classified as outliers. Extending beyond process discovery, there are many research efforts towards cleaning the event logs to deal with these outliers. In this paper, we present an approach that uses hidden Markov models to filter out outliers from event logs prior to applying any process discovery algorithms. Our proposed filtering approach can detect outlier behavior, and consequently, help process discovery algorithms return models that better reflect the real processes within an organization. Furthermore, we show that this filtering method outperforms two commonly used filtering approaches, namely the Matrix Filter approach and the Anomaly Free Automation approach for both artificial event logs and real-life event logs.

关键词： Automation Conferences Hidden Markov models Organizations filtering algorithms Information filters Cleaning

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Utilizing Various filtering Methodologies in Digital Image Processing

Utilizing Various Filtering Methodologies in Digital Image P...

引用

Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Harshdeep Singh Sarabpreet Kaur Preeti Sharma Institute of Engineering & Technology Punjab Chitkara University Punjab India Chandigarh Engineering College CGC Punjab India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

The development of efficient noise reduction techniques is imperative to maintain the quality and features of digital images, as they are essential in numerous key applications. Specifically, noise from salt and pepper can severely deteriorate the quality of digital images; the impact varies depending on the size and noise ratio of the image. The problem of image smoothing with edge preservation using Gaussian, mean, and median filters is addressed in this suggested work. For applications including computer vision, surveillance, and medical imaging, it seeks to preserve image structure while lowering noise. The results show that the Mean, Median, and Gaussian filters may be effectively compared for different smoothing applications, as indicated by the desirable peak signal to noise ratios (PSNR).

关键词： Salt Filters Smoothing methods PSNR Image edge detection Digital images Noise Noise reduction Adaptive filters filtering algorithms

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Design of $\alpha-\beta$ Digital filtering Algorithm for Foreign Object Detection in Wireless Charging System of Electric Vehicles

Design of $\alpha-\beta$ Digital Filtering Algorithm for For...

引用

International Conference on Power Electronics Systems and Applications (ICPESA)

作者： Jing Xiao Shaonan Chen Rui Ding Yuhong Mo Xiaorui Wu Wireless Power Transmission Joint Laboratory Southern Power Grid Corporation Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China College of Automation Chongqing University Chongqing China

ISBN: (数字)9798350365801

ISBN: (纸本)9798350365818

Currently, the detection of foreign objects in wireless charging of electric vehicles is usually carried out using auxiliary detection coils. However, the signals collected from the auxiliary detection coils under strong power fields after starting wireless charging have significant interference, and it is difficult to effectively restrain interference using hardware filtering. In this paper, a method based on α-β digital filtering is proposed to filter the amplitude and phase signals of foreign object detection under strong power magnetic field, so as to reduce signal interference and improve the reliability of foreign object detection. In this paper, a $\alpha-\beta$ digital filtering algorithm is designed and simulated, and compared with some common digital filtering algorithms, the results show that the AB digital filtering algorithm is better.

关键词： Coils filtering Inductive charging Interference Object detection filtering algorithms Electric vehicles

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Distributed Divided Difference filtering Based on Covariance Intersection over Sensor Network

Distributed Divided Difference Filtering Based on Covariance...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Pengfei Yang Xi Liu School of Systems Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper explores the distributed state estimation (DSE) for the nonlinear systems over a sensor network. Divided difference filtering (DDF) is one of the well-known sigma-point Kalman filtering algorithms, which can be categorized into the first-order divided difference (DD1) filter and the second-order divided difference (DD2) filter. Compared with the extended Kalman filter (EKF), DDF possesses numerous advantages. However, a corresponding distributed filtering algorithm has yet to be developed. Therefore, this paper combines the covariance intersection (CI) fusion algorithm and DDF to propose two distributed DDF type consensus algorithms, called the covariance intersection-based first-order divided difference (CI-DD1) filter and the covariance intersection-based second-order divided difference (CI-DD2) filter, which retain the advantages of distributed filters and the DDF. The effectiveness of the two proposed algorithms is demonstrated via a typical air traffic control scenario.

关键词： Target tracking Automation filtering Simulation Consensus algorithm filtering algorithms Kalman filters

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Analysis of Improved Algorithm for Digital filtering in Micro controller System

Analysis of Improved Algorithm for Digital Filtering in Micr...

引用

Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), IEEE International Conference on

作者： Jian Yang Sichuan University Jinjiang College Sichuan Province China

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

In order to solve the challenge of improved algorithm analysis of digital filtering in single-chip microcomputer system, in view of the shortcomings of the existing clustering analysis algorithms, an improved algorithm analysis method based on D-P algorithm based on D-P algorithm is introduced. This new scheme uses the principle of overlapping sub-problem theory to accurately identify and locate the key influencing factors, and accordingly carries out a wise classification of indicators to reduce possible interference. At the same time, using the unique mechanism of the D-P algorithm, the proposed scheme cleverly constructs an improved design strategy for digital filtering. The empirical results show that the proposed scheme shows a significant improvement compisd with the traditional clustering analysis algorithm in terms of the accuracy of the analysis of the improved algorithm of digital filtering, the processing efficiency of key factors and other key performance indicators, showing its obvious strong advantages. In the MCU system, the improved algorithm analysis of digital filtering plays a vital role, which can accurately predict and optimize the growth trend and output results of the improved algorithm analysis of the digital filtering of the MCU system. However, in the face of complex simulation tasks, traditional clustering algorithms show some inherent shortcomings, especially when dealing with multi-level challenges, their performance is often unsatisfactory. To overcome this problem, this study introduces a new idea of improved algorithm analysis of digital filtering optimized by D-P algorithm, and accurately controls the influencing parameters through the overlapping sub-problem theory, which is used as the road map for index allocation, and then uses the D-P algorithm to innovate and construct a system scheme. The test results clearly point out that in the context of the evaluation criteria, the new scheme has been significantly optimized in terms of a

关键词： Accuracy filtering Key performance indicator Clustering algorithms Microcomputers filtering algorithms Prediction algorithms

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Improved Kalman filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

引用

International Symposium on Autonomous Systems (ISAS)

作者： Ruidong Xie Pei Zhu Wenle Ma Zheqi Zhang Yingmin Yi Zheng Guo Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors.

关键词： Crystal growth filtering Noise Decision making Crystals Production filtering algorithms

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Research on software system for high performance hydrogen storage management system 3

Research on software system for high performance hydrogen st...

引用

2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023

作者： Zhang, Su Yang, Xiaoping Lin, Xuebing Inner Mongolir Power Machinery Reserrch Institute Hohhot China

ISBN: (纸本)9798350341546

The high-pressure hydrogen storage management system is an important part of the hydrogen-fueled vehicle, and the temperature, pressure and concentration of the hydrogen in the hydrogen storage cylinder will directly affect the safe driving of the vehicle. According to the analysis of the analog data collected by the hydrogen management controller, the data characteristics are obtained, and the collected temperature, pressure and concentration analog quantities are processed using different filtering algorithms. Based on the filtering algorithm, each analog quantity collected is independently collected, filtered, calculated, and limited, etc. Finally, the stability and reliability of the data are verified through experiments, so that in the event of an abnormal state of the hydrogen cylinder, the hydrogen management controller can provide timely warning and alarm to ensure the effective implementation of the safety control strategy. The controller provides timely warning and alarm to ensure the effective implementation of the safety control strategy. © 2023 IEEE.

关键词： filtering algorithms hydrogen storage management system analog acquisition

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De-speckling of Synthetic Aperture Radar Image using Hybrid filtering Techniques

De-speckling of Synthetic Aperture Radar Image using Hybrid ...

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International Conference for Convergence of Technology (I2CT)

作者： ShilpaVatkar Sujata Kulkarni Department of Electronics and Telecommunication Sardar Patel Institute of Technology Andheri Mumbai India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

For SAR de-speckling, two hybrid filtering algorithms based on the bilateral filter (BF), edge-based adaptive mean filter (EAM) and non-local mean filter (NLM) are presented in this work. The non-local filtering principle is used to choose the neighborhood that will be used for the estimation of the filtered pixels. The suggested system performances are evaluated and contrasted with current SAR de-speckling techniques. According to the results, the proposed hybrid filters outperformed the Frost and Median filters in terms of reducing speckles and preserving edge detail.

关键词： Measurement filtering Image edge detection Noise reduction Adaptive filters filtering algorithms Speckle

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