Researchers have developed and tested an infrared spectroscopy system that can rapidly detect chemical aerosols from a ...
Previous apps for identifying animal calls regularly hit practical limits: Without a stable internet connection, real-time ...
In the field of science and engineering, identifying the nonlinear dynamics of systems from data is a significant yet challenging task. In practice, the collected data are often contaminated by noise, ...
An essential step in the progression of nonlinear system identification is the inception of recurrent and convolution-type deep learning methods in industrial units. Many chemical/pharmaceutical/wa ...
Centre for Membrane Separations, Adsorption, Catalysis, and Spectroscopy for Sustainable Solutions, Department of Microbial and Molecular Systems, KU Leuven, Celestijnenlaan 200F, 3001 Leuven, Belgium ...
This Research Topic comprises five articles submitted and selected within “Linear Parameter Varying Systems Modelling, Identification and Control.” Linear parameter varying (LPV) systems are linear ...
The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor ...
Machine learning methods have revolutionized studies in several areas of knowledge, helping to understand and extract information from experimental data. Recently, these data-driven methods have also ...
Since the beginning of the pandemic, healthcare workers have administered billions of COVID-19 vaccine doses. In this Special Feature, we speak with medical experts about how scientists made ...
Abstract: This brief develops a robust multiple model strategy for nonlinear system identification with system output data corrupted by outliers. The nonlinear system is described as a global model ...
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