Abstract: This article investigates a novel robust Kalman filter (RKF) by incorporating kernel density estimation (KDE) in the Kalman filtering framework to address the disturbance of measurement ...
NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...
Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...
--lineage=NAME Specify lineage (optional) --outputdir=DIR Output directory (default: creates folder next to input file) --density-xlim=N Density plot X-axis limit (default: 1400) --neighbor-xlim=N ...
ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...
ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...
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