Pattern Theory : From representation to inference

Ulf ( Grenander

ISBN 10: 0198505701 / ISBN 13: 9780198505709

Edité par Oxford University Press Dez 2006, 2006

A propos de cet article

Neuware - Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computerscience, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website.The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometrictransformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum.Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look atinference, exploring random sampling approaches for estimation of model order and parametric representing of shapes.

N° de réf. du vendeur 9780198505709

Détails bibliographiques

• Titre: Pattern Theory : From representation to inference
• Éditeur: Oxford University Press Dez 2006
• Date de parution: 2006
• Langue: anglais
• ISBN à 10 chiffres: 0198505701
• ISBN à 13 chiffres: 9780198505709
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 251 L x 195 H x 30 P (en millimètres) 251 millimètres de largeur par 195 millimètres de hauteur par 30 millimètres de profondeur
• Poids: 1518 grammes

A propos de ce titre

Synopsis

Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website.
The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes.

À propos de l?auteur

Ulf Grenander is the L. Herbert Ballou University Professor at Brown University. He is a member of the Royal Swedish Academy of Science and an honorary fellow of the Royal Statistical Society in London


Michael Miller is the Professor of Electrical and Computer Engineering, Director of the Center for Imaging Science, and Professor of Biomedical Engineering at Johns Hopkins University, Baltimore. He completed his Ph.D. in Biomedical Engineering at The Johns Hopkins University in 1983.