Scientists discover that planetary system TOI-201 is changing its orbital structure, revealing to astronomers the role of ...

AI images and video may be impressive, but they’re not ‘professional’-standard – an issue that a new research project seeks ...

The Kolb Learning Cycle is a popular model of experiential learning in which agents move through four phases: experimentation, concretization, observation, and conceptualization. This model is a ...

Proper bearing selection depends on load analysis, speed requirements, precision needs, and environmental conditions to ensure system reliability and efficiency. Ball bearings offer high precision and ...

Using highly sophisticated switching linear dynamical systems (SLDS) analyses applied to functional MRI data, this study provides important insights into network dynamics underlying threat processing.

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology. The AI ...

Abstract: Sparsity constraints on the control inputs of a linear dynamical system naturally arise in several practical applications such as networked control, computer vision, seismic signal ...

Implementing (in Python) and performing ablation studies for Chen and Poor's algorithm for learning mixtures of linear dynamical systems.

Data and code for the paper "Coherent streamflow variability in Monsoon Asia over the past eight centuries---links to oceanic drivers" ...

Abstract: Accurately detecting the transient signal of interest from the background signal is one of the fundamental tasks in signal processing. The most recent approaches assume the existence of a ...