Results 71 to 80 of about 35,356 (190)

Adaptive Kalman Filter: Noise Reduction in Diagonal Drawings on Stylus/Pen Touchscreens for Enhanced Precision

Scientific Journal of King Faisal University: Basic and Applied Sciences
The adaptive Kalman filtering algorithm, designed to accommodate the dynamic nature of the system, provides an adaptive estimation of the state by incorporating both process and measurement noise considerations, thereby effectively reducing the noise and
Summiya Parveen
doaj   +1 more source

Adaptive ensemble Kalman filtering of non-linear systems

Tellus: Series A, Dynamic Meteorology and Oceanography, 2013
A necessary ingredient of an ensemble Kalman filter (EnKF) is covariance inflation, used to control filter divergence and compensate for model error. There is an on-going search for inflation tunings that can be learned adaptively.
Tyrus Berry, Timothy Sauer
doaj   +1 more source

Adaptive Neural Unscented Kalman Filter

eight pages, ten ...
Levy, Amit, Klein, Itzik
openaire   +2 more sources

Innovation-based adaptive Kalman filter derivation

2009 International Siberian Conference on Control and Communications, 2009
In this paper we develop innovation-based adaptive Kalman filter (IAKF) based on linear time-varying (LTV) state-space model. Thorough argumentation of process and measurement noise covariance adaptation based on innovation sequence covariance is provided.
Fokin L.A., Shchipitsyn A.G.
openaire   +2 more sources

An Efficient Kalman Noise Canceller for Cardiac Signal Analysis in Modern Telecardiology Systems

IEEE Access, 2018
The monitoring of electrocardiography (ECG) in ambulatory conditions is an important task for achieving success in remote healthcare monitoring. In this paper, Kalman-based adaptive artifact cancellation structures, which are the hybrid versions of least-
Asiya Sulthana, Md. Zia Ur Rahman, Shafi Shahsavar Mirza   +2 more
doaj   +1 more source

Detection of abrupt changes in dynamic systems [PDF]

Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered.
Willsky, A. S.
core   +1 more source

A Dual Filter Based on Radial Basis Function Neural Networks and Kalman Filters with Application to Numerical Wave Prediction Models

Sensors
The aim of this study is to introduce and evaluate a dual filter that combines Radial Basis Function neural networks and Kalman filters to enhance the accuracy of numerical wave prediction models.
Athanasios Donas, Ioannis Kordatos, Alex Alexandridis, George Galanis, Ioannis Th. Famelis   +4 more
doaj   +1 more source

Adaptive MSSRCPF filtering based on constrained optimization and fading memory for SINS/GNSS integrated navigation

Measurement + Control
To address particle degeneracy and the challenge of selecting importance density functions in traditional particle filters for complex nonlinear systems, we propose an adaptive mixed-order spherical simplex-radial cubature particle filter algorithm based
Ning Wang, Fanming Liu
doaj   +1 more source

Improved Adaptive Estimation Approach for Aircraft and Land Vehicle Applications

IEEE Access
A precise dynamic model and exact statistical information are required in a standard Kalman filter to ensure optimal performance. Without these, degraded performance may be obtained.
Chen Jiang, Dongbao Zhao, Zhen Li, Renwei Ding   +3 more
doaj   +1 more source