Overview
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Explore the mathematical foundations of Classical Least Squares and its variants in this 52-minute seminar by José Amigo Rubio. Delve into Weighted Least Squares, Generalized Least Squares, Extended Least Squares, and aspects of Multivariate Curve Resolution. Examine practical applications, including detecting ultratraces of micro and nanoplastics in sediments and biological materials, downweighting intra-class variance in NIR spectra of leaves as a preprocessing technique, and establishing new analytical detection limits. Learn about hyperspectral imaging, clutter reduction, optimization techniques, spectral angle mapping, and local solutions. Gain insights into the pros, cons, and limitations of these methods, and understand when to apply them effectively in data analysis and signal processing.
Syllabus
Introduction
Motivation
Project
Results
Hyperspectral Imaging
Clutter
Equations
Classical Least Square
Generalized Least Square
Matlab
Microparticles
Net Analyze Signal
Optimization
Spectra
Spectral Angle Mapping
Real Data
Local Solutions
Spectral Resolution
Limitations
Pros Cons
Methods
Questions
When
Conclusion
Taught by
Chemometrics & Machine Learning in Copenhagen