Results 81 to 90 of about 4,548 (274)

Estimation of FBMC/OQAM Fading Channels Using Dual Kalman Filters

The Scientific World Journal, 2014
We address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM) wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS) estimator or the minimum mean square error ...
Mahmoud Aldababseh, Ali Jamoos
doaj   +1 more source

Nowcasting World Trade With Machine Learning: A Three‐Step Approach

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn, Baptiste Meunier, Sebastian Stumpner   +2 more
wiley   +1 more source

Obstacle detection in aerodrome areas through the use of computer vision [PDF]

, 2010
This thesis addresses the problem of ground collisions between an aircraft and obstacles (including other aircraft) on the ramp and taxiway regions of an aireld.
Gauci, Jason
core  

Improving frequency and ROCOF accuracy during faults, for P class Phasor Measurement Units [PDF]

, 2013
Many aspects of Phasor Measurement Unit (PMU) performance are tested using the existing (and evolving) IEEE C37.118 standard. However, at present the reaction of PMUs to power network faults is not assessed under C37.118.
Roscoe, Andrew, Burt, Graeme, Rietveld, Gert, Gert Rietveld, Andrew J. Roscoe, Graeme M. Burt   +5 more
core   +1 more source

A Semi‐Automated Microfluidic Platform Employing Machine Learning Analysis to Study Adhesion Kinetics in Acute Myeloid Leukemia

Microscopy Research and Technique, EarlyView.
We have developed a semi‐automated shear flow platform using bright‐field optics and a machine‐learning analysis algorithm to dissect tumor‐microenvironment interactions. The algorithm quantifies the extent of adhesion at the single‐cell level and delivers consistent results within minutes instead of hours, facilitating high‐throughput analysis ...
Driti Ashok, Dennis Raith, Gabriel Kalweit, Maria Kalweit, Anusha Klett, Justus Duyster, Jonas Bermeitinger, Tanja Nicole Hartmann   +7 more
wiley   +1 more source

Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters [PDF]

, 2010
Prediction intervals in State Space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, where the true parameters are substituted by consistent estimates.
Ruiz Ortega, Esther, Rodríguez, Alejandro, Ruiz, Esther   +2 more
core  

Comparison of different kalman filters for tracking nonlinear transmission torques [PDF]

, 2004
This paper presents parameter estimation of physical time-varying parameters for a mechanical system with a nonlinear gear-box transmission torque. Four different variants of the Kalman filter are compared extensively on models of different complexities.
Geir Hovland, Hovland, Geir, Hovland, G. E.   +2 more
core   +1 more source

Recovering steady‐state visual evoked potential‐related electroencephalography during amplitude‐modulated‐transcranial alternating current stimulation using dynamic adaptive stimulation artifact source separation

Journal of Intelligent Medicine, EarlyView.
Abstract Simultaneous electroencephalography (EEG) recording during transcranial alternating current stimulation (tACS) is strongly contaminated by stimulation artifacts, limiting direct assessment of neural activity. Steady‐state visual evoked potentials (SSVEPs) provide frequency‐specific and phase‐locked responses, making them suitable for ...
Hongzuo Chu, Junling Wang, Xiaoya Liu, Sitong Chen, Tao Wang, Shuang Liu   +5 more
wiley   +1 more source

Vehicle state estimation based on Kalman filters [PDF]

, 2019
Vehicle state estimation represents a prerequisite for ADAS (Advanced Driver-Assistant Systems) and, more in general, for autonomous driving. In particular, algorithms designed for path or trajectory planning require the continuous knowledge of some data
M. Bersani, M. Vignati, S. Mentasti, Arrigoni S., Mentasti S., Vignati M., Cheli F., S. Arrigoni, F. Cheli, Bersani M.   +9 more
core   +1 more source

Noise-Adaptive State Estimators with Change-Point Detection

Sensors
Aiming at tracking sharply maneuvering targets, this paper develops novel variational adaptive state estimators for joint target state and process noise parameter estimation for a class of linear state-space models with abruptly changing parameters.
Xiaolei Hou, Shijie Zhao, Jinjie Hu, Hua Lan   +3 more
doaj   +1 more source