Results 101 to 110 of about 48,416 (251)

Consensus Based Strong Tracking Adaptive Cubature Kalman Filtering for Nonlinear System Distributed Estimation

IEEE Access, 2019
The distributed cubature Kalman filter is widely used in the field of target tracking, however, the presence of model uncertainties will undermine its tracking stability and effectiveness for tracking maneuvering target. In order to eliminate this effect
Zheng Zhang, Qingdong Li, Liang Han, Xiwang Dong, Yuan Liang, Zhang Ren   +5 more
doaj   +1 more source

Distributed Consensus Student-t Filter for Sensor Networks With Heavy-Tailed Process and Measurement Noises

IEEE Access, 2020
In the estimation of distributed sensor networks, process noise and measurement noise may have outliers which have heavy-tailed characteristics. To solve this problem, this paper proposes a distributed consensus estimating method for sensor networks ...
Jinran Wang, Peng Dong, Kai Shen, Xun Song, Xiaodong Wang   +4 more
doaj   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

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, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Hybrid Kalman Filtering Algorithm With Stochastic Nonlinearities and Multiple Missing Measurements

IEEE Access, 2019
In this paper, the hybrid Kalman filter is designed for a class of special nonlinear systems where the state equation is nonlinear and the measurement equation is linear.
Kemao Ma, Long Xu, Hongxia Fan
doaj   +1 more source

Regime‐Dependent Nowcasting of the Austrian Economy

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley   +1 more source

k-medoids-Trust-Based Distributed H_∞ Fusion Filtering Method [PDF]

Jisuanji gongcheng
To address the issues during system state estimation in the presence of node failures or anomalies in Wireless Sensor Networks (WSNs), a k-medoids-trust-based distributed H∞ fusion filtering method is proposed to improve the robustness and accuracy of ...
ZHU Hongbo, GAO Yanshen
doaj   +1 more source

The Impact of Uncertainty on Forecasting the US Economy

Journal of Forecasting, EarlyView.
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley   +1 more source

Distributed asynchronous measurement system fusion estimation based on inverse covariance intersection algorithm

Scientific Reports
For state estimation of multi-source asynchronous measurement systems with measurement missing phenomena, this paper proposes a distributed sequential inverse covariance intersection (DSICI) fusion algorithm based on conditional Kalman filtering method ...
Taishan Guo, Mingquan Wang, Shuyu Zhou, Wenai Song   +3 more
doaj   +1 more source

Distributed Filtering for Networked Stochastic Nonlinear Systems With Fading Measurements and Random Packet Dropouts

IEEE Access
In practical application scenarios, the phenomena of nonlinearity and missing data are commonly present in networked multi-sensor systems. Therefore, this paper investigates distributed filtering problems for networked stochastic nonlinear systems with ...
Hao Jin, Zuoqiang Du, Jing Ma
doaj   +1 more source

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Journal of Forecasting, EarlyView.
ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
wiley   +1 more source