Results 231 to 240 of about 63,163 (313)
Post-Processing Kalman Filter Application for Improving Cooperative Awareness Messages' Position Data Accuracy. [PDF]
Bauder M +3 more
europepmc +1 more source
Infants Recognized Other‐Race Faces When Learning Them With Incidental Emotional Sounds
ABSTRACT Infant face recognition shows plasticity, with recent evidence indicating enhancement by the presence of emotional facial expressions. The mechanisms and domain‐generality of this effect remain largely unknown. This study tested whether auditory emotional cues (vocalizations) facilitated infants' recognition of other‐race faces, a perceptual ...
Carie Guan +3 more
wiley +1 more source
An adaptive extended Kalman filter observer-for permanent magnet synchronous motor position sensorless control systems. [PDF]
Yingjun S, Zhenglong W, Yuanyuan F.
europepmc +1 more source
A High‐Precision SOH Estimation Solution Targeted at Electric Vehicle Power Batteries. ABSTRACT Accurately estimating the state of health (SOH) of power batteries is beneficial for their maintenance, delaying aging, ensuring safety, and providing a basis for their secondary use to enhance resource utilization efficiency.
Shan FengWu +6 more
wiley +1 more source
A Hybrid Soft Sensor Approach Combining Partial Least-Squares Regression and an Unscented Kalman Filter for State Estimation in Bioprocesses. [PDF]
Hermann L, Kremling A.
europepmc +1 more source
openaire +1 more source
Nonlinear Power Transfer Matrix Model for Power Control and Modeling of PMSG‐Wind Turbines ABSTRACT This paper presents the Lyapunov stability scheme based nonlinear power transfer matrix (NLPTM) model for controlling and modeling the permanent magnet synchronous generator (PMSG) based wind turbine.
Muhammad Ali Bijarani +5 more
wiley +1 more source
UltraTimTrack: a Kalman-filter-based algorithm to track muscle fascicles in ultrasound image sequences. [PDF]
van der Zee TJ +3 more
europepmc +1 more source
Augmenting Neural Networks With Time‐Varying Weights
ABSTRACT In the macroeconomic forecasting community, there is increasing interest in machine learning methods that can extract nonlinear predictive content from large datasets with a high number of predictors. Meanwhile, time‐varying parameter (TVP) models are known to flexibly model time series by allowing regression coefficients to vary over time ...
William Rudd +2 more
wiley +1 more source

