Chemometrics pattern recognition methods

Yun Xu

ISBN 10: 3659262099 / ISBN 13: 9783659262098

Published by LAP LAMBERT Academic Publishing Okt 2012, 2012

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -During my Ph.D study I had been challenged by many pattern recognition tasks which coming from very different disciplines. Each task had it's unique problems. It took great efforts to find a suitable way to solve each of the problem. In return, this thesis has covered a very broad spectrum of Chemometrics pattern recognition techniques, from well known and commonly used models such as PCA, PLS-DA to state of the art models such as kernel learning and support vector machines. There is also a good coverage of the methods which are much less known to the community but could be very useful methods such as principal coordiante analysis, featureless pattern recognitions and multivariate pattern comparison. The usefulness of these methods were demonstrated through several real-life applications including single nucleotide polymorphism analysis, DNA microarray analysis and a few human and mice metabolomic profiling studies. The comprehensive coverage of chemometrics pattern recognition techniues combined with several applications could be very useful to those who work in a similar discipline.Books on Demand GmbH, Überseering 33, 22297 Hamburg 268 pp. Englisch.

Seller Inventory # 9783659262098

Bibliographic Details

• Title: Chemometrics pattern recognition methods
• Publisher: LAP LAMBERT Academic Publishing Okt 2012
• Publication Date: 2012
• Language: English
• ISBN 10: 3659262099
• ISBN 13: 9783659262098
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 17D millimeters 220 millimeters width by 150 millimeters height by 17 millimeters depth
• Weight: 417 grams

About this title

Synopsis

During my Ph.D study I had been challenged by many pattern recognition tasks which coming from very different disciplines. Each task had it's unique problems. It took great efforts to find a suitable way to solve each of the problem. In return, this thesis has covered a very broad spectrum of Chemometrics pattern recognition techniques, from well known and commonly used models such as PCA, PLS-DA to state of the art models such as kernel learning and support vector machines. There is also a good coverage of the methods which are much less known to the community but could be very useful methods such as principal coordiante analysis, featureless pattern recognitions and multivariate pattern comparison. The usefulness of these methods were demonstrated through several real-life applications including single nucleotide polymorphism analysis, DNA microarray analysis and a few human and mice metabolomic profiling studies. The comprehensive coverage of chemometrics pattern recognition techniues combined with several applications could be very useful to those who work in a similar discipline.

About the Author

Dr Yun Xu started his career as an analytical chemist, obtained his B.Sc in Pharmaceutical analytical chemistry. He had worked in Institute for Drug Control of Wuhan City for 4 years. Then he decided to pursue a Ph.D in Chemometrics which is a subject. After obtaining his Ph.D he is working as a PDRA in University of Manchest.