Results 81 to 90 of about 15,255 (305)
Wavelet ensemble Kalman filters [PDF]
Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011 4 pages, 4 ...
Jonathan D. Beezley +2 more
openaire +2 more sources
Challenges with bearings only tracking for missile guidance systems and how to cope with them. [PDF]
, 2010 This paper addresses the problem of closed loop missile guidance using bearings and target angular extent information. Comparison is performed between particle filtering methods and derivative free methods.
Mihaylova, Lyudmila +2 more
core
UWB Indoor Positioning with Kalman Filters
, 2023 This thesis explores the application of Kalman Filters to Ultra-Wideband (UWB) indoor positioning systems (IPS), addressed through two primary research questions: "How can Kalman Filters be used in UWB indoor positioning?" and "How do different Kalman ...
Mäkipää, Antti-Jussi
core
Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which
Chen, Rong, Liu, Jun S.
openaire +2 more sources
Near-optimal kalman filters for multiparameter singularly perturbed linear systems [PDF]
, 2003 In this brief, we study the near-optimal Kalman filtering problem for multiparameter singularly perturbed system (MSPS). The attention is focused on the design of the near-optimal Kalman filters.
Mukaidani, Hiroaki
core +1 more source
Deep Underground Science and Engineering, EarlyView.This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu +4 more
wiley +1 more source
Spatio‐Temporal Dual‐Encoder Transformer for Short‐Term Regional Wind Power Forecasting
Energy Science &Engineering, EarlyView.ST‐DualFormer separates temporal and spatial encoding to model complex dependencies in regional wind power forecasting. The fused dual‐stream representation enables accurate short‐term regional forecasts from multi‐farm meteorological and historical power data. The method achieved 5.25% nMAE and 7.53% nRMSE for three‐day‐ahead forecasting on real‐world
Jianfeng Che +4 more
wiley +1 more source
Precision planter monitoring system based on mobile communication network
IET Networks, EarlyView., 2022 Abstract Sowing is an important link in agricultural production and the basis for ensuring high yields and bumper harvests. Agriculture requires precision plows with good performance and stable work. However, the seeding process is in a completely closed state, and the operator relies mainly on experience to judge the operating state and performance of
Bing Li, Jiyun Li
wiley +1 more source
An Introduction to Kalman Filters
Measurement + Control, 1986 Kalman filters are a powerful tool for reducing the effects of noise in measurements. This paper gives a no-nonsense introduction to the subject for people with A-level maths.
G C Dean
doaj +1 more source