SIMPLE aerodynamic configurations under even modest conditions can exhibit complex
flows with a wide range of temporal and spatial features. It has become common practice in …

Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …

The dynamic mode decomposition (DMD) has become a leading tool for data-driven
modeling of dynamical systems, providing a regression framework for fitting linear dynamical …

Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow
analysis, and reduced-order modeling. In situations where a system is time varying, one …

Randomized numerical linear algebra-RandNLA, for short-concerns the use of
randomization as a resource to develop improved algorithms for large-scale linear algebra …

Matrix decompositions are fundamental tools in the area of applied mathematics, statistical
computing, and machine learning. In particular, low-rank matrix decompositions are vital …

This paper presents a randomized algorithm for computing the near-optimal low-rank
dynamic mode decomposition (DMD). Randomized algorithms are emerging techniques to …

Gait is considered an attractive biometric identifier for its non-invasive and non-cooperative
features compared with other biometric identifiers such as fingerprint and iris. At present …

The Koopman theory, a concept to globally model nonlinear signals by a linear Hamiltonian,
has been at the frontier of fluid mechanics research for the last decade. Wind engineering …

Background estimation and foreground segmentation are important steps in many high-level
vision tasks. Many existing methods estimate background as a low-rank component and …