In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density ...

Abstract: Particle filters (PFs) are widely used for state estimation in signal processing. However, the standard PFs suffer from weight degeneracy and sample impoverishment. To overcome these, we ...

Turn Excel into a lightweight data-science tool for cleaning datasets, standardizing dates, visualizing clusters, and ...

This sample project shows how a Python application can be configured to send Semantic Kernel telemetry to the Application Performance Management (APM) vendors of your choice. In this sample, we ...

Bura, A.H. and Mung’onya, E.M. (2026) A Novel ICT-Enabled Decision Support Approach for Surveillance and Control of ...

Abstract: The response probability density function (PDF) fully characterizes the behavior of uncertain systems and serves as a critical metric in uncertainty quantification. Physical experiments for ...