Results 91 to 100 of about 15,255 (305)

Informativeness of Parallel Kalman Filters

, 2004
This article considers the informativeness of parallel Kalman filters. Expressions are derived for determination of the amount of information obtained by additional measurements with a reserved measurement channel during processing.
Chingiz Hajiyev
core   +1 more source

An adequacy‐for‐purpose perspective for the environmental sciences

Frontiers in Ecology and the Environment, EarlyView.
The range of datasets, methods, and other tools available for environmental research and decision‐making is rapidly expanding. How should the quality of these tools be evaluated? When are new resources better than existing resources? We advocate an adequacy‐for‐purpose perspective, according to which the quality of environmental research tools depends ...
Wendy S Parker, Cayelan C Carey, Freya Olsson, R Quinn Thomas   +3 more
wiley   +1 more source

Adaptive Measurement Noise for Robust Kalman Filtering in Smart Beehive Telemetry

IEEE Access
Honeybee colony monitoring generates multimodal, non-stationary telemetry streams that require reliable recursive state estimation with well-calibrated uncertainty for digital apiculture.
H. A. A. U. Ranasinghe, Navod Neranjan Thilakarathne, Jamil Abedalrahim Jamil Alsayaydeh, Rex Bacarra, Rostam Affendi Hamzah   +4 more
doaj   +1 more source

Geometry of Kalman Filters [PDF]

, 2012
In this paper is presented a geometric explanation of Kalman filters in terms of a symplectic linear space and a special quadratic form on it. It is an extension of the work of Bougerol with application of a different metric introduced earlier. The author's purpose in this paper is to show that both contraction properties can be understood purely in ...
openaire   +3 more sources

Localisation of mobile nodes in wireless networks with correlated in time measurement noise. [PDF]

, 2011
Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in ...
Bull, D.R., Angelova, D, Mihaylova, Lyudmila, Donka Angelova, Bull, David R., Canagarajah, Nishan, Canagarajah, C, Angelova, Donka, Nishan Canagarajah, Bull, DR, David Bull, Angelova, D., Canagarajah, N., Lyudmila Mihaylova, Mihaylova, LS, Mihaylova, L.   +15 more
core   +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

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

Journal of Forecasting, EarlyView.
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

Weighted Fusion Robust Steady-State Kalman Filters for Multisensor System with Uncertain Noise Variances

Journal of Applied Mathematics, 2014
A direct approach of designing weighted fusion robust steady-state Kalman filters with uncertain noise variances is presented. Based on the steady-state Kalman filtering theory, using the minimax robust estimation principle and the unbiased linear ...
Wen-Juan Qi, Peng Zhang, Zi-Li Deng
doaj   +1 more source

Robust Kalman Filtering [PDF]

, 2000
As already pointed out in Hardle, Klinke, and Muller (2000, Chapter 10), state-space models are very useful and flexible in the sense that various recursive methods for time-dependent situations can be formulated as general solutions of filtering, smoothing and prediction problems in state-space models.
openaire   +3 more sources

Kalman filtering with intermittent observations

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
Motivated by navigation and tracking applications within sensor networks, we consider the problem of performing Kalman filtering with intermittent observations. When data travel along unreliable communication channels in a large, wireless, multihop sensor network, the effect of communication delays and loss of information in the control loop cannot be ...
B. Sinopoli, SCHENATO, LUCA, M. Franceschetti, K. Poolla, M. Jordan, S. Sastry   +5 more
openaire   +1 more source