Results 111 to 120 of about 48,416 (251)
Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays
The optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays. The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described ...
Dongyan Chen, Long Xu
doaj +1 more source
Forecasting With Dynamic Factor Models Estimated by Partial Least Squares
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley +1 more source
Privacy-Preserving Distributed Kalman Filtering
Ashkan Moradi +3 more
openaire +2 more sources
A pilot variational coupled reanalysis based on the CESAM climate model
Variational data assimilation of in‐situ and satellite ocean data and reanalysis atmospheric data into an intermediate complexity Earth system model is possible by adjusting the surface fluxes and internal model parameters. This pilot application requires nearly complete information on the atmospheric state for synchronization.
Armin Köhl +6 more
wiley +1 more source
Bayesian filtering provides an effective approach for the orbit determination of a non‐cooperative target using angle measurements from multiple CubeSats.
Zhixun Zhang +4 more
doaj +1 more source
This work demonstrates the potential of the assimilation of satellite solar‐induced fluorescence (SIF) retrievals at eight‐day and 0.1° resolutions in the integrated forecast system (IFS), developed at the European Centre for Medium‐Range Weather Forecasts (ECMWF), at global scale, to provide a more realistic representation of the vegetation temporal ...
Sébastien Garrigues +12 more
wiley +1 more source
Communication-Efficient Distributed Kalman Filtering Using ADMM
This paper addresses the problem of optimal linear filtering in a network of local estimators, commonly referred to as distributed Kalman filtering (DKF). The DKF problem is formulated within a distributed optimization framework, where coupling constraints require the exchange of local state and covariance updates between neighboring nodes to achieve ...
Kumar Kundan +2 more
openaire +2 more sources
Though many studies have shown potential benefit in assimilating all‐sky infrared radiances from geostationary satellites, at numerical weather prediction centres it is still common practice to assimilate clear‐sky radiances. We present the operationalization of the all‐sky assimilation of the spinning enhanced visible and infrared imager (SEVIRI ...
Annika Schomburg +5 more
wiley +1 more source
Robust Estimation Fusion in Wireless Senor Networks with Outliers and Correlated Noises
This paper addresses the problem of estimation fusion in a distributed wireless sensor network (WSN) under the following conditions: (i) sensor noises are contaminated by outliers or gross errors; (ii) process noise and sensor noises are correlated; (iii)
Yan Zhou +3 more
doaj +1 more source
This article demonstrates that assimilating machine‐learning‐derived surface nitrate can improve five‐day phytoplankton forecast substantially within the Met Office operational system for the Northwest European Shelf. We explain the reasons behind this improvement and propose that an online system where machine learning and data assimilation are cycled
Deep S. Banerjee +2 more
wiley +1 more source

