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Pattern Recognition: Concepts, Methods and Applications

Autor J.P. Marques de Sá
en Limba Engleză Paperback – 5 dec 2012
Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity. The generally recognized relevance of pattern recognition methods and techniques lies, for the most part, in the general trend of "intelligent" task emulation, which has definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth's resources, and analysis of satellite data are just a few examples of activity fields where this trend applies. The pervasiveness of pattern recognition has boosted the number of task­ specific methodologies and enriched the number of links with other disciplines. As counterbalance to this dispersive tendency there have been, more recently, new theoretical developments that are bridging together many of the classical pattern recognition methods and presenting a new perspective of their links and inner workings. This book has its origin in an introductory course on pattern recognition taught at the Electrical and Computer Engineering Department, Oporto University. From the initial core of this course, the book grew with the intent of presenting a comprehensive and articulated view of pattern recognition methods combined with the intent of clarifying practical issues with the aid of examples and applications to real-life data. The book is primarily addressed to undergraduate and graduate students attending pattern recognition courses of engineering and computer science curricula.
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Specificații

ISBN-13: 9783642626777
ISBN-10: 3642626777
Pagini: 344
Ilustrații: XIX, 318 p. 198 illus., 3 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.48 kg
Ediția:Softcover reprint of the original 1st ed. 2001
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Graduate

Cuprins

1 Basic Notions.- 1.1 Object Recognition.- 1.2 Pattern Similarity and PR Tasks.- 1.3 Classes, Patterns and Features.- 1.4 PR Approaches.- 1.5 PR Project.- 2 Pattern Discrimination.- 2.1 Decision Regions and Functions.- 2.2 Feature Space Metrics.- 2.3 The Covariance Matrix.- 2.4 Principal Components.- 2.5 Feature Assessment.- 2.6 The Dimensionality Ratio Problem.- Exercises.- 3 Data Clustering.- 3.1 Unsupervised Classification.- 3.2 The Standardization Issue.- 3.3 Tree Clustering.- 3.4 Dimensional Reduction.- 3.5 K-Means Clustering.- 3.6 Cluster Validation.- Exercises.- 4 Statistical Classification.- 4.1 Linear Discriminants.- 4.2 Bayesian Classification.- 4.3 Model-Free Techniques.- 4.4 Feature Selection.- 4.5 Classifier Evaluation.- 4.6 Tree Classifiers.- 4.7 Statistical Classifiers in Data Mining.- Exercises.- 5 Neural Networks.- 5.1 LMS Adjusted Discriminants.- 5.2 Activation Functions.- 5.3 The Perceptron Concept.- 5.4 Neural Network Types.- 5.5 Multi-Layer Perceptrons.- 5.6 Performance of Neural Networks.- 5.7 Approximation Methods in NN Training.- 5.8 Genetic Algorithms in NN Training.- 5.9 Radial Basis Functions.- 5.10 Support Vector Machines.- 5.11 Kohonen Networks.- 5.12 Hopfield Networks.- 5.13 Modular Neural Networks.- 5.14 Neural Networks in Data Mining.- Exercises.- 6 Structural Pattern Recognition.- 6.1 Pattern Primitives.- 6.2 Structural Representations.- 6.3 Syntactic Analysis.- 6.4 Structural Matching.- Exercises.- Appendix A—CD Datasets.- A.1 Breast Tissue.- A.2 Clusters.- A.3 Cork Stoppers.- A.4 Crimes.- A.5 Cardiotocographic Data.- A.6 Electrocardiograms.- A.7 Foetal Heart Rate Signals.- A.8 FHR-Apgar.- A.9 Firms.- A.10 Foetal Weight.- A.11 Food.- A.12 Fruits.- A.13 Impulses on Noise.- A.14 MLP Sets.- A.15 Norm2c2d.- A.16 Rocks.- A.17 StockExchange.- A.18 Tanks.- A.19 Weather.- Appendix B—CD Tools.- B.1 Adaptive Filtering.- B.2 Density Estimation.- B.3 Design Set Size.- B.4 Error Energy.- B.5 Genetic Neural Networks.- B.6 Hopfield network.- B.7 k-NN Bounds.- B.8 k-NN Classification.- B.9 Perceptron.- B.10 Syntactic Analysis.- Appendix C—Orthonormal Transformation.- Appendix C—Orthonormal Transformation.

Recenzii

From the reviews of the first edition:
"The book gives an overview about the wide field of pattern recognition. … The book is primarily addressed to undergraduate and graduate students of engineering and computer science courses. It gives a good introduction into the field of clustering and pattern recognition." (Hans-Peter Altenburg, Zentralblatt MATH, Vol. 1009, 2003)
"‘Patern Recognition’ presents methods and techniques that are suitable for practical application in areas including robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth’s resources, and satellite data analysis. … This book provides comprehensive, non-specialist coverage of pattern recognition. Although primarily aimed at undergraduate and graduate engineering and computer science students, its clear and practical coverage also makes it suitable for physicians, biologists, geologists and economists." (Assembly Automation, Vol. 22 (4), 2002)

Textul de pe ultima copertă

The book provides a comprehensive view of Pattern Recognition concepts and methods, illustrated with real-life applications in several areas (e.g. engineering, medicine, economy, geology). It is appropriate as a textbook of Pattern Recognition courses and also for professionals and researchers who need to apply Pattern Recognition techniques. These are explained in a unified and innovative way, with multiple examples enhancing the clarification of concepts and the application of methods. Recent results in the main Pattern Recognition areas (Statistical Classification, Neural Networks and Structural Recognition) are presented. A CD offered with the book includes datasets and software tools, making it easier for the reader to follow the taught matters in a hands-on fashion right from the start.

Caracteristici

Unifying approach describing all relevant and recent methods Real-life problems in engineering, medicine, economy, geology solved in detail Guidance how to design PR systems and use software tools in practical applications Mathematics made easy CD-ROM with solved exercises and important software tools Includes supplementary material: sn.pub/extras