MATLAB® for Chemometricians, Volume 33 provides a complete introduction to the topic of MATLAB programming. Written by, and for, chemometricians, the book presents a very practical and task-oriented introduction on how to use MATLAB. Programming tips are contextualized within specific chemometric objectives, and each practical section is accompanied by theoretical background that describes the basic chemometrics concepts behind the algorithms for deeper understanding. The book starts from scratch (i.e., descriptions of the basic MATLAB layout and how to perform the most elementary algebraic…mehr
MATLAB® for Chemometricians, Volume 33 provides a complete introduction to the topic of MATLAB programming. Written by, and for, chemometricians, the book presents a very practical and task-oriented introduction on how to use MATLAB. Programming tips are contextualized within specific chemometric objectives, and each practical section is accompanied by theoretical background that describes the basic chemometrics concepts behind the algorithms for deeper understanding. The book starts from scratch (i.e., descriptions of the basic MATLAB layout and how to perform the most elementary algebraic operations) and leads readers through increasingly demanding tasks. Programming tricks are introduced when discussing specific problems in a concrete manner. Readers will not only be able to use existing chemometric toolboxes, but also to write and develop their own, even with the possibility of building graphical user interfaces.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Federico Marini is currently associate professor of Chemometrics at Sapienza University of Rome. In 2006, he was awarded the Young Researcher Prize from the Italian Chemical Society and in 2012 he won the Chemometrics and Intelligent Laboratory Systems Award. His research activity focuses on chemometrics, ranging from the application of existing methods to real world problems to the design and development of novel algorithms. He is author of more than 150 papers in international journals and book chapters, and recently he edited and coauthored the book Chemometrics in Food Chemistry (Elsevier). He is member of the Editorial boards of several journals, and he serves as Associate Editor for Chemometrics in Wiley's Encyclopedia of Analytical Chemistry. He is the past-coordinator of the Chemometric group of the Italian Chemical Society and a member of the Chemometric study group of EUCheMS.
Inhaltsangabe
Section I Basics 1. Introduction to the Matlab environment and data types 2. Simple algebraic operations 3. Basic Matrix Algebra 4. Univariate data analysis and first plotting commands Section II Multivariate analysis 5. From univariate to multivariate linear regression: starting working extensively with matrices 6. Introduction to Experimental Design: Generating factorial designs and 3D plotting 7. PCA and Exploratory analysis: Building model structures and a basic graphical user interface 8. Bilinear calibration (PCR and PLS): More on the algorithmic side 9. Classification: Building decision rules and advanced 2D and 3D plotting Section III Advanced material 10. Multivariate curve resolution: Introducing the ALS algorithm and simple constraints 11. Multi-way modelling: How to deal with multi-way arrays and how to process them 12. Signal processing: Derivatives, noise reduction, alignment 13. Image analysis: what you see and what you can get from it
Section I Basics 1. Introduction to the Matlab environment and data types 2. Simple algebraic operations 3. Basic Matrix Algebra 4. Univariate data analysis and first plotting commands Section II Multivariate analysis 5. From univariate to multivariate linear regression: starting working extensively with matrices 6. Introduction to Experimental Design: Generating factorial designs and 3D plotting 7. PCA and Exploratory analysis: Building model structures and a basic graphical user interface 8. Bilinear calibration (PCR and PLS): More on the algorithmic side 9. Classification: Building decision rules and advanced 2D and 3D plotting Section III Advanced material 10. Multivariate curve resolution: Introducing the ALS algorithm and simple constraints 11. Multi-way modelling: How to deal with multi-way arrays and how to process them 12. Signal processing: Derivatives, noise reduction, alignment 13. Image analysis: what you see and what you can get from it
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