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检索条件"主题词=Filtering algorithm"

共 185 条记录，以下是111-120 订阅

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Analysis of Time Domain Characteristic of Transformer On-load Tap-changer 6

Analysis of Time Domain Characteristic of Transformer On-loa...

引用

6th International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Yu Bing Zhao Lin Lin Haofan Yang Yong State Grid Zhejiang Elect Power Res Inst Hangzhou Peoples R China

ISBN: (纸本)9781665458863

On-load tap-changer is a switching device that provides a constant voltage for a transformer when the load changes. The basic principle is to realize the switching between taps in the transformer winding without interrupting the load current, thereby changing the number of winding turns, that is, the voltage ratio of the transformer, and finally achieving the purpose of voltage regulation. In this paper, the characteristic parameters are collected by time domain analysis method, which provides the basis for discriminating the later fault warning.

关键词： on-load tap-changer change-over switch selector adaptive morphology filtering algorithm wavelet transform

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Restoration of Information in On-Board Information and Controlling Complexes of Movable Objects in Emergency Situations 2

Restoration of Information in On-Board Information and Contr...

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2nd International Workshop on Modern Machine Learning Technologies and Data Science (MoMLeT+DS)

作者： Mashkov, Oleg Kosenko, Viktoriya State Ecol Acad Postgrad Educ & Management St Metropolitan Vasily Lipkivsky 35 UA-03035 Kiev Ukraine

The technology of estimation of efficiency of methods of information recovery in on-board information-control complexes of moving objects in emergency situations caused by failures of hardware and software parts of on-board information-control complexes is offered. The proposed approach is considered as one of the steps of ensuring the functional stability of complex dynamic objects. Functional stability is considered as a property of a dynamic system, which is the ability to perform at least a set volume of its functions when failures in the information, computing, energy parts of the system, as well as external influences that are not foreseen by the operating conditions. It is proposed to provide functional stability in real time by performing the following actions: control of the state of functioning of a complex management system and detection of the fact of disturbances of its functioning (formation of the team "Accident");identification of the cause of the fact of malfunctions in real time (localization of the place of damage of functioning and / or detection of unauthorized disturbances);shutting down the damaged parts or compensating for the effects of unauthorized disturbances on the general real-time control system;redistribution of system resources (information, computing, power) to ensure the functioning of the management system (possibly with impaired performance) in real time. It is determined that the implementation of functional stability can be achieved by the introduction into the complex dynamic system of various forms of redundancy (structural, functional, information, etc.) and the readiness of the operator of the dynamic object to control movement during a sudden reconfiguration of the complex. A mathematical model is proposed that allows you to build functional stability when using an automated control system for a complex dynamic object. The peculiarities of the application of the method of optimal filtration in emergencies caused by the evo

关键词： filtering algorithm On-Board Information-Control Complex Failures Information Recovery Dynamic System Identification Markov Chain Emergency Situation Optimal Filtration Functional Stability

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ESTIMATION OF WIDELY FACTORIZABLE HYPERCOMPLEX SIGNALS WITH UNCERTAIN OBSERVATIONS 44

ESTIMATION OF WIDELY FACTORIZABLE HYPERCOMPLEX SIGNALS WITH ...

引用

44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Fernandez-Alcala, R. M. Jimenez-Lopez, J. D. Navarro-Moreno, J. Ruiz-Molina, J. C. Le Bihan, N. Univ Jaen Dept Stat & Operat Res Campus Las Lagunillas Jaen 23071 Spain Univ Grenoble Alpes CNRS Grenoble INP Gipsa Lab F-38000 Grenoble France

ISBN: (纸本)9781479981311

The filtering estimation problem under uncertainty conditions is addressed for a class of improper quaternion signals, called widely factorizable, characterized because their augmented correlation function is a factorizable kernel. From the knowledge of the correlation functions involved, a recursive algorithm is designed for the computation of the widely linear (WL) filtering estimate and its associated mean squared error. The main advantage of the proposed solution is that it can be applied in situations where a state-space model is not readily at hand. The benefits of the proposed WL filtering algorithm is analyzed through a simulation example where WL filtering errors are compared with respect to the strictly linear (SL) counterparts, showing the superior behavior of the former over the latter.

关键词： Quaternion signals filtering algorithm uncertainty conditions widely factorizable signals widely linear processing

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Continuous-time Nonlinear Estimation Filters Using UKF-aided Gaussian Sum Representations

Continuous-time Nonlinear Estimation Filters Using UKF-aided...

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16th International Conference on Information Fusion (FUSION)

作者： Gokce, Murat Kuzuoglu, Mustafa Sci & Technol Res Council Turkey Technol & Innovat Funding Programs Directorate Ankara Turkey Middle East Tech Univ Dept Elect & Elect Engn Ankara Turkey

ISBN: (纸本)9786058631113

An approximate nonlinear estimation method for continuous-time systems with discrete-time measurements is developed. The approach evaluates the Gaussian sum approximation of the a priori probability density function (pdf) by solving the Fokker-Planck equation numerically. Approximate evaluation of the a posteriori pdf is achieved by using Gaussian sums, a priori pdf and measurements in Bayes rule. Mean and covariance values of Gaussians are chosen by the help of an Unscented Kalman Filter (UKF), with respect to a region where a priori and a posteriori pdfs are approximated. Weights of the Gaussians are updated using the deterministically chosen grid points in the specified domains. UKF here acts as a one step look ahead mechanism to determine the high probability regions where a priori and a posteriori pdfs can reside. The a priori and a posteriori pdfs are approximated around these high probability regions. The developed approach is compared with UKF and Particle Filter in a one dimensional nonlinear system.

关键词： nonlinear system filtering algorithm continuous-time system Fokker-Planck equation Gaussian sum numerical methods

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Unscented Kalman Filter for Higher Index Nonlinear Differential-Algebraic Equations 19

Unscented Kalman Filter for Higher Index Nonlinear Different...

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19th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Alkov, Ilja Weidemann, Dirk Univ Appl Sci Bielefeld Inst Syst Dynam & Mechatron Bielefeld Germany

ISBN: (纸本)9781479950812

This contribution concerns the unscented Kalman filter (UKF) for higher index nonlinear differential-algebraic equation (DAE) systems. First, a short introduction to DAE systems is given. A solution concept for nonlinear DAE systems is discussed focusing on properties which are essential for the application of the UKF algorithm. The introduction of a stochastic noise in DAE systems and the contrast to stochastic ordinary differential equations (ODE) are described subsequently. Further, the unscented Kalman filter algorithm is reviewed and former filtering approaches considering DAE systems are summarized. Finally, a direct generalized state estimation approach for higher index nonlinear DAE systems utilizing the UKF is proposed. Particularly, the estimation of the DAE inconsistent generalized state is permitted and several concepts for the consistent DAE initialization in the prediction step of the filtering algorithm are proposed. A simple example demonstrates the advantages of the proposed approach.

关键词： Kalman filters algebra nonlinear differential equations nonlinear filters DAE initialization DAE systems ODE UKF filtering algorithm higher index nonlinear differential-algebraic equations stochastic ordinary differential equations unscented Kalman filter Equations Estimation Indexes Mathematical model Noise Stochastic processes Kalman filters filtering algorithms Ordinary differential equation Nonlinear filters nonlinear differential equations Markov chain Algebra Mathematical Model differential algebraic equations Noise solution concept Stochastic Processes

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Performance of Drivable Path Detection System of Autonomous Robots in Rain and snow Scenario

Performance of Drivable Path Detection System of Autonomous ...

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1st International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Yinka, Agunbiade O. Ngwira, Selemon M. Tranos, Zuva Sengar, Prateek S. Tshwane Univ Technol Pretoria South Africa

ISBN: (纸本)9781479928668

Drivable path detection is an important factor to consider for a successful development of autonomous robot which is characterized as an intelligent vehicle. Researchers using different vision-based techniques have achieved remarkable result toward drivable path detection. Regardless of this achievement, environmental noise such as rain and/or snow can cause misdetection of drivable path which can lead to autonomous robot accident. In this paper, after investigating the effects of rain and/or snow, we introduced into the drivable path detection system a filtering algorithm that addresses the detection and removal of rain and/or snow for the optimization of the system. Experiments were carried out to show the effectiveness of the filter in the system. The results show that filtering algorithm assists the autonomous driving system in navigating perfectly during rain and/or snow scenario with minimal accident.

关键词： Autonomous robot Vision-based System filtering algorithm Environmental Noise and Navigation

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Near Field Distance Awareness algorithm using Bluetooth for Device Sociality Service 18

Near Field Distance Awareness Algorithm using Bluetooth for ...

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18th International Conference on Advanced Communication Technology (ICACT)

作者： Jung, Joon-young Kang, Dong-oh Choi, Jang-ho Min, Ok-gee Elect & Telecommun Res Inst Human Comp Res Sect Daejeon South Korea

ISBN: (纸本)9788996865063

The use of Device-to-Device (D2D) communication in various networks is expected to grow in the coming years. The D2D distance-based device sociality service is affected by distance awareness between the D2D devices. Thus, the wireless distance awareness between smart devices should be accomplished easily, accurately, and immediately. When smart devices are used in the distance-based distance sociality service, the smart device needs to know the distance to other smart devices in order to aware the space sociality. Several methods, such as receive signal strength indication (RSSI), time of arrival (ToA), and time difference of arrival (TDoA), can be used to aware the distance between D2D devices. Among these methods, the RSSI system can aware the D2D distance easily and inexpensively because most smart devices can estimate the received signal strength. However, estimating the distance using a RSSI is difficult due to inaccuracies. We conducted a preliminary test to discover the relationship between the actual distance and a Bluetooth RSSI under near field environment. Through the results of this test, we realize that the near field distance is hard to be classified due to the inaccuracy of Bluetooth RSSI. Therefore, in this paper, the near field distance awareness algorithm is proposed to reduce measurement errors by alleviating fluctuations in a Bluetooth signal. To evaluate the effectiveness of the proposed algorithm, the distance awareness is compared using different filtering algorithms, such as, a low-pass filer (LPF), a Kalman filter, and a particle filter under a meeting room environment. The proposed algorithm showed the best results in terms of the coefficient of determination, standard deviation, and measurement range.

关键词： Near field awareness Device to Device (D2D) Distance awareness filtering algorithm Wireless signal

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Image Enhancement from Illumination Variation to Improve the Performance of Simultaneous Localization and Mapping Technique 4

Image Enhancement from Illumination Variation to Improve the...

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4th International Conference on Information and Computer Technologies (ICICT)

作者： Agunbiade, O. Y. Zuva, T. Vaal Univ Technol Dept Informat Technol Vanderbijlpk ZA-1900 Gauteng South Africa

ISBN: (纸本)9781665413992

The Simultaneous Localization and Mapping (SLAM) is a research problem that has been explored by scholars. The SLAM contribution to autonomous robot navigation has attracted the attention of many researchers and over the decades, many SLAM techniques with outstanding achievement has been presented to resolve the SLAM problem. However, there are factors such as environmental noises that can limit the performance of SLAM techniques. These environmental noises can create misunderstandings in image analysis with an erroneous effect on the robot navigation path. In this study, attention will only focus on shadow and light intensity environmental noise and in resolving this issue, filters were presented to modify the original Monte Carlo algorithm to improve its effectiveness. MATLAB was used for the simulation experiment and evaluation is based on qualitative and quantitative methods. The experimental results acquired were compared to the original Monte Carlo algorithm without filters and the results obtained were amazing. The accomplishment of the modified Monte Carlo algorithm has led to enhancement in robot path and in real-life implementation will facilitate self-directed navigation, exploration, and route planning while it decreases accident rates and injuries for human working in an unstable environment.

关键词： Autonomous robot Trajectory Navigation filtering algorithm Kidnap problem Dynamic Environment Simultaneous Localization and Mapping

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Research on scene parsing algorithm cascading object detection network 20

Research on scene parsing algorithm cascading object detecti...

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20th IEEE International Conference on Computational Science and Engineering (CSE) / 15th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC)

作者： Guo, Xi Wen, Yuanzhen Ma, Dongyuan Jin, Yuhui Yu, Haitao Beihang Univ Sch Software Beijing 100191 Peoples R China Tencent Technol Shenzhen LI Shenzhen 518057 Peoples R China Transportat Informat Ctr Beijing 100073 Peoples R China

ISBN: (纸本)9781538632215

Using deep learning for visual scene parsing will satisfy the demand of the next generation of automatic driving technology. However, current parsing algorithms are not mature enough for practical applications unless higher accuracy and efficiency are obtained. We propose a novel scene parsing algorithm framework which integrates the object detection technologies into convolution neural network to improve the overall effectiveness. The framework consists of three components: i) a scene parsing network presenting primary semantic segmentation result. ii) an object detection network calculating the location and confidence of the targets in images. iii) an integration and filter module that cascades previous two results. Extensive experiments suggest that our model is capable of practical use and achieving more favorable scene parsing performance of mIoU score as 69.4% on CamVid dataset.

关键词： scene parsing object detection filtering algorithm

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A new parameters adaptively adjusting method of current statistical model

A new parameters adaptively adjusting method of current stat...

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IEEE International Conference on Information and Automation 2015

作者： Yang, Yongjian Fan, Xiaoguagn Wang, Shengda Zhuo, Zhenfu Nan, Jianguo Huang, Lei Air Force Engn Univ Aeronaut & Astronaut Engn Coll Xian 710038 Shannxi Provinc Peoples R China

ISBN: (纸本)9781467391047

The fixed maximum acceleration and maneuvering frequency of current statistical model leads to the divergence of filtering algorithm. In this study, a new model which employs innovation dominated subjection function to adaptively adjust maximum acceleration and maneuvering frequency is proposed based on current statistical model. Although the new model has a better performance, a fluctuant phenomenon appears. As far as this problem is concerned, a new filter algorithm which is based on amendatory and adaptively fading kalman filtering is proposed. The results of simulation indicate the effectiveness and coherent of the new model and the new algorithm, and their well performance in maneuvering target tracking.

关键词： current statistical model filtering algorithm maneuvering target tracking

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