Chemometrics pattern recognition (33 résultats)

Hardcover. Etat : Fine. 1st Edition. A very clean book from the Lederle Laboratories Library. If not for the spine label & card pouch this book would be labled New! Text has No Markings, No Underlining, No Highlighting. Nice.

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Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Paperback. Etat : Brand New. 268 pages. 8.66x5.91x0.61 inches. In Stock.

Etat : New. This is the only major text in the area of chemometrics published over the last decade focusing exclusively on pattern recognition. The coverage uses real world pattern recognition case studies, often involving quite large and complex datasets. Num Pages: 522 pages, Illustrations. BIC Classification: PBT; PNF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 250 x 175 x 31. Weight in Grams: 1286. . 2009. 1st Edition. Hardcover. . . . .…

Etat : New. pp. xvii + 504 Illus. (Col.).

Etat : New. In English.

Gebunden. Etat : New. Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of d.

Etat : New. pp. xvii + 504 Index.

Hardcover. Etat : Brand New. 1st edition. 522 pages. 10.00x7.00x1.25 inches. In Stock.

Etat : New. This is the only major text in the area of chemometrics published over the last decade focusing exclusively on pattern recognition. The coverage uses real world pattern recognition case studies, often involving quite large and complex datasets. Num Pages: 522 pages, Illustrations. BIC Classification: PBT; PNF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 250 x 175 x 31. Weight in Grams: 1286. . 2009. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Etat : Neu. Neuware - Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: - 'Real world' pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; - Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; - Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; - Representation in full colour; - Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.…

Etat : Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Taschenbuch. Etat : Neu. Chemometrics pattern recognition methods | Applications to gentics and metabolomics data | Yun Xu | Taschenbuch | 268 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659262098 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - 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. 268 pp. Englisch.…

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Xu YunDr 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 Chemome.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…