Chemical Applications of Pattern Recognition
Author: Peter C. Jurs
Publisher: Wiley-Interscience
Published: 1975
Total Pages: 200
ISBN-13:
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Author: Peter C. Jurs
Publisher: Wiley-Interscience
Published: 1975
Total Pages: 200
ISBN-13:
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Publisher:
Published: 1976
Total Pages: 136
ISBN-13:
DOWNLOAD EBOOKAuthor: Jahan B. Ghasemi
Publisher: Elsevier
Published: 2022-10-20
Total Pages: 212
ISBN-13: 0323907067
DOWNLOAD EBOOKMachine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis. Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data Discusses the use of machine learning for recognizing patterns in multidimensional chemical data Identifies common sources of multivariate errors
Author: William Sacco
Publisher:
Published: 1977
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Oldřich Štrouf
Publisher: Wiley-Blackwell
Published: 1986
Total Pages: 234
ISBN-13:
DOWNLOAD EBOOKAuthor: Kurt Varmuza
Publisher:
Published: 1980-11-01
Total Pages: 240
ISBN-13: 9783642931567
DOWNLOAD EBOOKAuthor: Kurt Varmuza
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 232
ISBN-13: 3642931553
DOWNLOAD EBOOKAnalytical chemistry of the recent years is strongly influenced by automation. Data acquisition from analytica~ instruments - and some times also controlling of instruments - by a computer are principally solved since many years. Availability of microcomputers made these tasks also feasible from the economic point of view. Besides these basic applications of computers in chemical measurements scientists developed computer programs for solving more sophisticated problems for which some kind of "intelligence" is usually supposed to be necessary. Harm less numerical experiments on this topic led to passionate discussions about the theme "which jobs cannot be done by a computer but only by human brain ?~. If this question is useful at all it should not be ans wered a priori. Application of computers in chemistry is a matter of utility, sometimes it is a social problem, but it is never a question of piety for the human brain. Automated instruments and the necessity to work on complex pro blems enhanced the development of automatic methods for the reduction and interpretation of large data sets. Numerous methods from mathematics, statistics, information theory, and computer science have been exten sively investigated for the elucidation of chemical information; a new discipline "chemometrics" has been established. Three different approaches have been used for computer-assisted interpretations of chemical data. 1. Heuristic methods try to formu late computer programs working in a similar way as a chemist would solve the problem. 2.
Author: Nels H. Mahle
Publisher:
Published: 1974
Total Pages: 274
ISBN-13:
DOWNLOAD EBOOKAuthor: Burgos, Diego Alexander Tibaduiza
Publisher: IGI Global
Published: 2019-12-27
Total Pages: 357
ISBN-13: 1799818411
DOWNLOAD EBOOKThe implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking. Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.
Author: Barton Paul Simmons
Publisher:
Published: 1991
Total Pages: 274
ISBN-13:
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