Results 11 to 20 of about 9,465 (199)

An improved Epidemiological-Unscented Kalman Filter (Hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data [PDF]

Chaos, Solitons & Fractals, 2022
This article has been published in the journal Chaos, Solitons & Fractals with the title " An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data "
Vasileios Ε. Papageorgiou, George Tsaklidis   +1 more
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A Code for Unscented Kalman Filtering on Manifolds (UKF-M) [PDF]

2020 IEEE International Conference on Robotics and Automation (ICRA), 2020
The present paper introduces a novel methodology for Unscented Kalman Filtering (UKF) on manifolds that extends previous work by the authors on UKF on Lie groups. Beyond filtering performance, the main interests of the approach are its versatility, as the method applies to numerous state estimation problems, and its simplicity of implementation for ...
Martin Brossard, Axel Barrau, Silvère Bonnabel   +2 more
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Mechanical speed estimation of a DFIG based on the Unscented Kalman Filter (UKF)

International Journal of Energetica, 2022
This work proposes a new estimation technique for the doubly-fed induction generator (DFIG) variables. Researchers have designed numerous sensorless control strategies for the DFIG used either for mechanical speed, electromagnetic torque, or rotor position estimation.
Hicham Ben Sassi, Khadija Lahrech, Fatima Errahimi, Najia Es-Sbai, Mokhtar Ghodbane   +4 more
openalex   +5 more sources

Unscented Kalman filter (UKF)–based nonlinear parameter estimation for a turbulent boundary layer: a data assimilation framework [PDF]

Measurement Science and Technology, 2020
Abstract A turbulent boundary layer is a ubiquitous element of fundamental and applied fluid mechanics. Unfortunately, accurate measurements of turbulent boundary layer parameters (e.g. friction velocity
Zhao Pan, Yang Zhang, Jonas P R Gustavsson, Jean-Pierre Hickey, Louis N Cattafesta III   +4 more
openalex   +4 more sources

The Intuitive Supervision Model (ISM) using Convolution Neural Networks (CNN) and Unscented Kalman Filters (UKF)

International Journal of Recent Technology and Engineering (IJRTE), 2022
Radio frequency identification technology is one of the fastest-growing technologies in the realms of navigation, medical, robotics, communication system, logistics, security, safety, etc. Surveillance is one of the important fields where high accuracy and fast response are needed.
Noopur Soni, Agya Mishra
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Data-Driven Intrusion Detection in Vehicles: Integrating Unscented Kalman Filter (UKF) with Machine Learning [PDF]

Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics
Accepted in Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 714-723.
Shuhao Bian, Milad Farsi, Nasser L. Azad, Chris Hobbs   +3 more
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State Estimation of the Vinyl Acetate Reactor Using Unscented Kalman Filters (UKF) [PDF]

2005 International Conference on Industrial Electronics and Control Applications, 2006
The main objective of our research is to develop several unscented transform techniques (UTT) to estimate the state of the nonlinear processes such as an improvement of an extended Kalman filter (EKF) approach. The extended Kalman filter (EKF) has become a standard nonlinear estimation technique in control systems and parameter estimation for nonlinear
Nicolae Tudoroiu, K. Khorasani
openalex   +3 more sources

Accuracy Improvement of RSSI-based Distance Localization using Unscented Kalman Filter (UKF) Algorithm for Wi-Fi Tracking Application

International Journal of Interactive Mobile Technologies (iJIM), 2020
<p class="0abstract">In this report, we perform the digital filter computation using Matlab for Wi-Fi tracking application. This work motivates to improve the accuracy of filter algorithm in the RSSI-based distance localization system. There are several aspects that we can improve, e.g., in the Filter part and Path-loss model.
Syifaul Fuada, Trio Adiono, Prasetiyo Prasetiyo   +2 more
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UKF‐MOT: An unscented Kalman filter‐based 3D multi‐object tracker [PDF]

CAAI Transactions on Intelligence Technology
Abstract Multi‐object tracking in autonomous driving is a non‐linear problem. To better address the tracking problem, this paper leveraged an unscented Kalman filter to predict the object's state. In the association stage, the Mahalanobis distance was employed as an affinity metric, and a Non‐minimum Suppression method was designed ...
Meng Liu, Jianwei Niu, Yu Liu
openalex   +3 more sources

A Cost-Effective Vehicle Localization Solution Using an Interacting Multiple Model−Unscented Kalman Filters (IMM-UKF) Algorithm and Grey Neural Network [PDF]

Sensors, 2017
In this paper, we propose a cost-effective localization solution for land vehicles, which can simultaneously adapt to the uncertain noise of inertial sensors and bridge Global Positioning System (GPS) outages. First, three Unscented Kalman filters (UKFs) with different noise covariances are introduced into the framework of Interacting Multiple Model ...
Qimin Xu, Xu Li, Ching‐Yao Chan
openalex   +7 more sources