Download or read book An Investigation of Chemical Pattern Recognition Methodologies written by Anthony J. Myles and published by . This book was released on 2005 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Chemical Pattern Recognition written by Oldřich Štrouf and published by Wiley-Blackwell. This book was released on 1986 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling written by Jahan B. Ghasemi and published by Elsevier. This book was released on 2022-10-20 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine 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
Download or read book Proceedings of the Workshop on Chemical Applications of Pattern Recognition Washington D C May 1 2 1975 written by and published by . This book was released on 1976 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Chemometrics for Pattern Recognition written by Richard G. Brereton and published by John Wiley & Sons. This book was released on 2009-09-28 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Pattern Recognition Approach to Data Interpretation written by Diane Wolff and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: An attempt is made in this book to give scientists a detailed working knowledge of the powerful mathematical tools available to aid in data interpretation, especially when con fronted with large data sets incorporating many parameters. A minimal amount of com puter knowledge is necessary for successful applications, and we have tried conscien tiously to provide this in the appropriate sections and references. Scientific data are now being produced at rates not believed possible ten years ago. A major goal in any sci entific investigation should be to obtain a critical evaluation of the data generated in a set of experiments in order to extract whatever useful scientific information may be present. Very often, the large number of measurements present in the data set does not make this an easy task. The goals of this book are thus fourfold. The first is to create a useful reference on the applications of these statistical pattern recognition methods to the sciences. The majority of our discussions center around the fields of chemistry, geology, environmen tal sciences, physics, and the biological and medical sciences. In Chapter IV a section is devoted to each of these fields. Since the applications of pattern recognition tech niques are essentially unlimited, restricted only by the outer limitations of.
Download or read book Pattern Recognition in Chemistry written by Kurt Varmuza and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analytical 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.
Download or read book Methodologies of Pattern Recognition written by Satosi Watanabe and published by Academic Press. This book was released on 2014-05-12 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures, and the implications of interactive graphic computers for pattern recognition methodology. Some papers describe non-supervised learning in statistical pattern recognition, parallel computation in pattern recognition, and statistical analysis as a tool to make patterns emerge from data. One paper points out the importance of cluster processing in visual perception in which proximate points of similar brightness values form clusters. At higher levels of mental activity humans are efficient in clumping complex items into clusters. Another paper suggests a recognition method which combines versatility and an efficient noise-proofness in dealing with the two main problems in the field of recognition. These difficulties are the presence of a large variety of observed signals and the presence of interference. One paper reports on a possible feature selection for pattern recognition systems employing the minimization of population entropy. Electronic engineers, physicists, physiologists, psychologists, logicians, mathematicians, and philosophers will find great rewards in reading the above collection.
Download or read book Potential Pattern Recognition in Chemical and Medical Decision Making written by D. Coomans and published by Research Studies Press Limited. This book was released on 1986 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multivariate Pattern Recognition in Chemometrics written by R.G. Brereton and published by Elsevier. This book was released on 1992-09-04 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemometrics originated from multivariate statistics in chemistry, and this field is still the core of the subject. The increasing availability of user-friendly software in the laboratory has prompted the need to optimize it safely. This work comprises material presented in courses organized from 1987-1992, aimed mainly at professionals in industry. The book covers approaches for pattern recognition as applied, primarily, to multivariate chemical data. These include data reduction and display techniques, principal components analysis and methods for classification and clustering. Comprehensive case studies illustrate the book, including numerical examples, and extensive problems are interspersed throughout the text. The book contains extensive cross-referencing between various chapters, comparing different notations and approaches, enabling readers from different backgrounds to benefit from it and to move around chapters at will. Worked examples and exercises are given, making the volume valuable for courses. Tutorial versions of SPECTRAMAP and SIRIUS are optionally available as a Software Supplement, at a low price, to accompany the text.
Download or read book The Application of Pattern Recognition Techniques to Data Derived from the Chemical Analysis of Common Wax Based Products and Ignitable Liquids written by Dzulkiflee Ismail and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is a term that can be used to cover various stages of the investigation of characterising data sets including contributing to problem formulation and data collection through to discrimination, assessment and interpretation of results. Chemometrics techniques and Artificial Neural Networks (ANNs) are pattern recognition techniques commonly used to visualise and gather useful information from multidimensional datasets i.e. datasets with n-samples with m- variables. Of the many chemometric techniques available, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) are the most commonly used in the evaluation of dataset(s) generated from the analysis of samples which have relevance to forensic science. By contrast, Artificial Neural Networks (ANNs) and in particular Self Organising Feature Maps (SOFM) and Multi Layer Perceptron (MLP) have had limited application in forensic science eventhough these pattern recognition techniques have been known for almost 30 years. This study focuses on the applicability of the Artificial Neural Networks (ANNs) to specific datasets of forensic science interest and compares these with 'conventional' PCA and HCA techniques. Datasets generated from the analysis of wax based products and lighter fuels were used. The wax based product data set contained information obtained from Thin Layer Chromatography (TLC), Microspectrophotometry (MSP), Ultra-Violet and Visible Spectroscopy (UV/Vis) and Gas Chromatography with Flame Ionisation Detector (GC-FID) analysis of a variety of products from multiple sources where discrimination by brand was the objective. The data provided for the lighter fuel samples was obtained from analysis of a number of brands, both unevaporated and evaporated by Gas Chromatography-Mass Spectroscopy (GC-MS) and the objective was to discriminate the samples by brand as well as link degraded samples from the same brand together. The wax based product analysis provided simple, straight forward data whilst the lighter fuel analysis provided a more complicated and challenging dataset to investigate in terms of facilitating sample discrimination and/or linkage. In all cases, the 'conventional' Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) failed to provide any meaningful discrimination of the samples by product type regardless of the nature of the datasets. In contrast, the Artificial Neural Networks (ANNs) techniques provided full discrimination of the samples by product type even when the samples had undergone considerable ageing and weathering. This work has demonstrated the potential use of Self Organising Feature Maps (SOFM) and Multi Layer Perceptron (MLP) to datasets of forensic science relevance. The findings of this work provide avenues for further exploration of Artificial Neural Networks (ANNs) in forensic science.
Download or read book Pattern Recognition written by Bruce G. Batchelor and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is a child of modern technology; electronics and computers in particular have inspired research and made it possible to develop the subject in a way which would have been impossible otherwise. It is a rapidly growing research field which began to flourish in the 1960s and which is beginning to produce commercial devices. Significant developments have been made, both in the theory and practical engineering of the subject, but there is evidence of a schism developing between these two approaches. Practical machines have usually been designed on an ad hoc basis, with little use being made of advanced theory. It is difficult to provide a rigorous mathematical treatment of many problems pertinent to a practical situation. This is due, in part at least, to a conceptual rift between theory and practice. The mathematics of optimal systems is well developed, whereas pragmatists are more concerned with vaguer ideas of reasonable and sufficient. In some situations, the quest for optimality can constrain research and retard practical progress. This can occur, for example, if too narrow a view is taken of "optimal": the accuracy of a system may be optimal whereas its speed, cost, or physical size may be grossly suboptimal. The objective of this book is to present a glimpse of the pragmatic approach to pattern recognition; there already exist a number of excellent texts describing theoretical developments.
Download or read book Four Studies in Chemical Pattern Recognition Using a Data Structural Approach to Problem Solving and Method Development written by Alice Marion Harper and published by . This book was released on 1978 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Pattern Recognition written by Andrzej Zak and published by BoD – Books on Demand. This book was released on 2019-07-31 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition, despite its relatively short history, has already found practical application in many areas of human activity. Systems of pattern recognition usually support people in performing tasks related to ensuring security, including access to premises and devices, detection of unusual changes (e.g. in medicine, cartography, geology), diagnosing technical conditions of devices, and many others. Nevertheless, pattern recognition is probably the most developing area because of the great demand for such solutions in the different areas of our lives. In this book we have collected the experience of scientists from different parts of the world who have researched diverse areas connected directly or indirectly with pattern recognition. We hope that this book will be a treasure trove of knowledge and inspiration for further research in the field of pattern recognition.
Download or read book Chemometrics for Pattern Recognition written by Richard G. Brereton and published by John Wiley & Sons. This book was released on 2009-06-29 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Pattern Recognition From Classical To Modern Approaches written by Sankar Kumar Pal and published by World Scientific. This book was released on 2001-11-23 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.
Download or read book Pattern Recognition Applications in Engineering written by Burgos, Diego Alexander Tibaduiza and published by IGI Global. This book was released on 2019-12-27 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 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.
