On the implementation of spatial constraints in multivariate curve resolution alternating least squares for hyperspectral image analysis

2015 ◽  
Vol 29 (10) ◽  
pp. 557-561 ◽  
Author(s):  
Siewert Hugelier ◽  
Olivier Devos ◽  
Cyril Ruckebusch
Keyword(s):  
Image Analysis ◽  
Least Squares ◽  
Hyperspectral Image ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Spatial Constraints ◽  
Curve Resolution ◽  
Hyperspectral Image Analysis

Multivariate curve resolution for hyperspectral image analysis: applications to microarray technology

2003 ◽  
Author(s):  
David M. Haaland ◽  
Jerilyn A. Timlin ◽  
Michael B. Sinclair ◽  
Mark H. Van Benthem ◽  
M. Juanita Martinez ◽  
...  
Keyword(s):  
Image Analysis ◽  
Hyperspectral Image ◽  
Multivariate Curve Resolution ◽  
Microarray Technology ◽  
Curve Resolution ◽  
Hyperspectral Image Analysis

scholarly journals Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS)

2015 ◽  
Vol 10 (2) ◽  
pp. 217-240 ◽  
Author(s):  
Judith Felten ◽  
Hardy Hall ◽  
Joaquim Jaumot ◽  
Romà Tauler ◽  
Anna de Juan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Least Squares ◽  
Biological Material ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Curve Resolution

scholarly journals Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)

2019 ◽  
Vol 69 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban
Keyword(s):  
Least Squares ◽  
Water Samples ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Least Squares Regression ◽  
Environmental Matrices ◽  
Curve Resolution ◽  
Real Water Samples ◽  
Target Analytes ◽  
Spectrophotometric Data

Abstract The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous resolution and quantification of ketoprofen, naproxen, paracetamol and caffeine as target analytes and triclosan as an interfering component in different water samples using UV-Vis spectrophotometric data. A multivariate regression model using the partial least squares regression (PLSR) algorithm was developed and calculated. The MCR-ALS results were compared with the PLSR obtained results. Both models were validated on external sample sets and were applied to the analysis of real water samples. Both models showed comparable and satisfactory results with the relative error of prediction of real water samples in the range of 1.70–9.75 % and 1.64–9.43 % for MCR-ALS and PLSR, resp. The obtained results show the potential of MCR-ALS with correlation constraint to be applied for the determination of different pharmaceuticals in complex environmental matrices.

Sign in / Sign up

Export Citation Format

Share Document