Abstract: This article introduces a novel signal parameterization approach, termed nonlinear Schur-type signal parameterization, designed to enhance machine learning tasks such as signal ...

Beneath the ocean surface mixed layer (ML), shear-generated turbulence is a critical mechanism driving mixing and vertical transport in stably stratified environmental flows (Geyer et al., 2010; Smyth ...

ABSTRACT: This paper investigates the combination of the sliding mode control (SMC) and standard extended state observer (SESO) methods for estimating the states of a Photovoltaic system associated ...

Abstract: Dataset distillation is an emerging dataset reduction method, which condenses large-scale datasets while maintaining task accuracy. Current parameterization methods achieve enhanced ...

To reduce the loss of human lives and damage to property caused by typhoon disasters, it is crucial to continuously improve numerical models and enhance their capacity to forecast typhoon tracks and ...

The Njord Centre, Department of Physics, University of Oslo, Sem Sælands vei 24, NO-0316 Oslo, Norway ...

Electrochemical impedance spectroscopy (EIS) provides valuable insights into the physical processes within batteries – but how can these measurements directly inform physics-based models? In this ...

As a passionate fan of MUI Datatables, I’ve continued the development of this project out of appreciation for its simplicity and power, especially after the original repository was no longer ...

Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter ...