Image Models (and their Speech Model Cousins)

Image Models (and their Speech Model Cousins)

Author: Stephen Levinson

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 208

ISBN-13: 1461240565

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This IMA Volume in Mathematics and its Applications IMAGE MODELS (AND THEIR SPEECH MODEL COUSINS) is based on the proceedings of a workshop that was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We thank Stephen E. Levinson and Larry Shepp for organizing the workshop and for editing the proceedings. We also take this opportunity to thank the National Science Foundation, the Army Research Office, and the National Security Agency, whose financial support made the workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE This volume is an attempt to explore the interface between two diverse areas of applied mathematics that are both "customers" of the maximum likelihood methodology: emission tomography (on the one hand) and hid den Markov models as an approach to speech understanding (on the other hand). There are other areas where maximum likelihood is used, some of which are represented in this volume: parsing of text (Jelinek), microstruc ture of materials (Ji), and DNA sequencing (Nelson). Most of the partici pants were in the main areas of speech or emission density reconstruction. Of course, there are many other areas where maximum likelihood is used that are not represented here.


Book Synopsis Image Models (and their Speech Model Cousins) by : Stephen Levinson

Download or read book Image Models (and their Speech Model Cousins) written by Stephen Levinson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications IMAGE MODELS (AND THEIR SPEECH MODEL COUSINS) is based on the proceedings of a workshop that was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We thank Stephen E. Levinson and Larry Shepp for organizing the workshop and for editing the proceedings. We also take this opportunity to thank the National Science Foundation, the Army Research Office, and the National Security Agency, whose financial support made the workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE This volume is an attempt to explore the interface between two diverse areas of applied mathematics that are both "customers" of the maximum likelihood methodology: emission tomography (on the one hand) and hid den Markov models as an approach to speech understanding (on the other hand). There are other areas where maximum likelihood is used, some of which are represented in this volume: parsing of text (Jelinek), microstruc ture of materials (Ji), and DNA sequencing (Nelson). Most of the partici pants were in the main areas of speech or emission density reconstruction. Of course, there are many other areas where maximum likelihood is used that are not represented here.

Image Models (and Their Speech Model Cousins)

Image Models (and Their Speech Model Cousins)

Author: Stephen Levinson

Publisher:

Published: 1996-08-01

Total Pages: 220

ISBN-13: 9781461240570

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Book Synopsis Image Models (and Their Speech Model Cousins) by : Stephen Levinson

Download or read book Image Models (and Their Speech Model Cousins) written by Stephen Levinson and published by . This book was released on 1996-08-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Image Models (and their Speech Model Cousins)

Image Models (and their Speech Model Cousins)

Author: Stephen Levinson

Publisher: Springer Science & Business Media

Published: 1996-08-29

Total Pages: 228

ISBN-13: 9780387948065

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This volume explores the interface between two diverse areas of applied mathematics which are both 'customers' of the maximum likelihood methodology; emission tomography and hidden Markov models as an approach to speech understanding. Other areas where maximum likelihood is used in this volume include parsing of text (Jelinek), microstructure of materials (Ji), DNA sequencing (Nelson). Most of the participants were in the main areas of speech or emission density reconstruction.


Book Synopsis Image Models (and their Speech Model Cousins) by : Stephen Levinson

Download or read book Image Models (and their Speech Model Cousins) written by Stephen Levinson and published by Springer Science & Business Media. This book was released on 1996-08-29 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the interface between two diverse areas of applied mathematics which are both 'customers' of the maximum likelihood methodology; emission tomography and hidden Markov models as an approach to speech understanding. Other areas where maximum likelihood is used in this volume include parsing of text (Jelinek), microstructure of materials (Ji), DNA sequencing (Nelson). Most of the participants were in the main areas of speech or emission density reconstruction.

Pattern Theory

Pattern Theory

Author: Ulf Grenander

Publisher: Oxford University Press

Published: 2007

Total Pages: 633

ISBN-13: 0198505701

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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.


Book Synopsis Pattern Theory by : Ulf Grenander

Download or read book Pattern Theory written by Ulf Grenander and published by Oxford University Press. This book was released on 2007 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Discrete Tomography

Discrete Tomography

Author: Gabor T. Herman

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 491

ISBN-13: 1461215684

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Goals of the Book Overthelast thirty yearsthere has been arevolutionindiagnostic radiology as a result oftheemergenceofcomputerized tomography (CT), which is the process of obtaining the density distribution within the human body from multiple x-ray projections. Since an enormous variety of possible density values may occur in the body, a large number of projections are necessary to ensure the accurate reconstruction oftheir distribution. There are other situations in which we desire to reconstruct an object from its projections, but in which we know that the object to be recon structed has only a small number of possible values. For example, a large fraction of objects scanned in industrial CT (for the purpose of nonde structive testing or reverse engineering) are made of a single material and so the ideal reconstruction should contain only two values: zero for air and the value associated with the material composing the object. Similar as sumptions may even be made for some specific medical applications; for example, in angiography ofthe heart chambers the value is either zero (in dicating the absence of dye) or the value associated with the dye in the chamber. Another example arises in the electron microscopy of biological macromolecules, where we may assume that the object to be reconstructed is composed of ice, protein, and RNA. One can also apply electron mi croscopy to determine the presenceor absence ofatoms in crystallinestruc tures, which is again a two-valued situation.


Book Synopsis Discrete Tomography by : Gabor T. Herman

Download or read book Discrete Tomography written by Gabor T. Herman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Goals of the Book Overthelast thirty yearsthere has been arevolutionindiagnostic radiology as a result oftheemergenceofcomputerized tomography (CT), which is the process of obtaining the density distribution within the human body from multiple x-ray projections. Since an enormous variety of possible density values may occur in the body, a large number of projections are necessary to ensure the accurate reconstruction oftheir distribution. There are other situations in which we desire to reconstruct an object from its projections, but in which we know that the object to be recon structed has only a small number of possible values. For example, a large fraction of objects scanned in industrial CT (for the purpose of nonde structive testing or reverse engineering) are made of a single material and so the ideal reconstruction should contain only two values: zero for air and the value associated with the material composing the object. Similar as sumptions may even be made for some specific medical applications; for example, in angiography ofthe heart chambers the value is either zero (in dicating the absence of dye) or the value associated with the dye in the chamber. Another example arises in the electron microscopy of biological macromolecules, where we may assume that the object to be reconstructed is composed of ice, protein, and RNA. One can also apply electron mi croscopy to determine the presenceor absence ofatoms in crystallinestruc tures, which is again a two-valued situation.

A First Course in Optimization

A First Course in Optimization

Author: Charles L. Byrne

Publisher: CRC Press

Published: 2014-08-11

Total Pages: 318

ISBN-13: 1482226561

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Give Your Students the Proper Groundwork for Future Studies in Optimization A First Course in Optimization is designed for a one-semester course in optimization taken by advanced undergraduate and beginning graduate students in the mathematical sciences and engineering. It teaches students the basics of continuous optimization and helps them better understand the mathematics from previous courses. The book focuses on general problems and the underlying theory. It introduces all the necessary mathematical tools and results. The text covers the fundamental problems of constrained and unconstrained optimization as well as linear and convex programming. It also presents basic iterative solution algorithms (such as gradient methods and the Newton–Raphson algorithm and its variants) and more general iterative optimization methods. This text builds the foundation to understand continuous optimization. It prepares students to study advanced topics found in the author’s companion book, Iterative Optimization in Inverse Problems, including sequential unconstrained iterative optimization methods.


Book Synopsis A First Course in Optimization by : Charles L. Byrne

Download or read book A First Course in Optimization written by Charles L. Byrne and published by CRC Press. This book was released on 2014-08-11 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Give Your Students the Proper Groundwork for Future Studies in Optimization A First Course in Optimization is designed for a one-semester course in optimization taken by advanced undergraduate and beginning graduate students in the mathematical sciences and engineering. It teaches students the basics of continuous optimization and helps them better understand the mathematics from previous courses. The book focuses on general problems and the underlying theory. It introduces all the necessary mathematical tools and results. The text covers the fundamental problems of constrained and unconstrained optimization as well as linear and convex programming. It also presents basic iterative solution algorithms (such as gradient methods and the Newton–Raphson algorithm and its variants) and more general iterative optimization methods. This text builds the foundation to understand continuous optimization. It prepares students to study advanced topics found in the author’s companion book, Iterative Optimization in Inverse Problems, including sequential unconstrained iterative optimization methods.

A Stochastic Grammar of Images

A Stochastic Grammar of Images

Author: Song-Chun Zhu

Publisher: Now Publishers Inc

Published: 2007

Total Pages: 120

ISBN-13: 1601980604

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A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.


Book Synopsis A Stochastic Grammar of Images by : Song-Chun Zhu

Download or read book A Stochastic Grammar of Images written by Song-Chun Zhu and published by Now Publishers Inc. This book was released on 2007 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.

Iterative Optimization in Inverse Problems

Iterative Optimization in Inverse Problems

Author: Charles Byrne

Publisher: CRC Press

Published: 2014-02-12

Total Pages: 298

ISBN-13: 1482222345

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Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent work that has not appeared in other books and draws on the author's considerable research in the field, including his recently developed class of SUMMA algorithms


Book Synopsis Iterative Optimization in Inverse Problems by : Charles Byrne

Download or read book Iterative Optimization in Inverse Problems written by Charles Byrne and published by CRC Press. This book was released on 2014-02-12 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent work that has not appeared in other books and draws on the author's considerable research in the field, including his recently developed class of SUMMA algorithms

Stochastic Models in Geosystems

Stochastic Models in Geosystems

Author: Stanislav A. Molchanov

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 496

ISBN-13: 1461385008

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This IMA Volume in Mathematics and its Applications STOCHASTIC MODELS IN GEOSYSTEMS is based on the proceedings of a workshop with the same title and was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We would like to thank Stanislav A. Molchanov and Wojbor A. Woyczynski for their hard work in organizing this meeting and in edit ing the proceedings. We also take this opportunity to thank the National Science Foundation, the Office of N aval Research, the Army Research Of fice, and the National Security Agency, whose financial support made this workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE A workshop on Stochastic Models in Geosystems was held during the week of May 16, 1994 at the Institute for Mathematics and Its Applica tions at the University of Minnesota. It was part of the Special Year on Emerging Applications of Prob ability program put together by an organiz ing committee chaired by J. Michael Steele. The invited speakers represented a broad interdisciplinary spectrum including mathematics, statistics, physics, geophysics, astrophysics, atmo spheric physics, fluid mechanics, seismology, and oceanography. The com mon underlying theme was stochastic modeling of geophysical phenomena and papers appearing in this volume reflect a number of research directions that are currently pursued in these areas.


Book Synopsis Stochastic Models in Geosystems by : Stanislav A. Molchanov

Download or read book Stochastic Models in Geosystems written by Stanislav A. Molchanov and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications STOCHASTIC MODELS IN GEOSYSTEMS is based on the proceedings of a workshop with the same title and was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We would like to thank Stanislav A. Molchanov and Wojbor A. Woyczynski for their hard work in organizing this meeting and in edit ing the proceedings. We also take this opportunity to thank the National Science Foundation, the Office of N aval Research, the Army Research Of fice, and the National Security Agency, whose financial support made this workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE A workshop on Stochastic Models in Geosystems was held during the week of May 16, 1994 at the Institute for Mathematics and Its Applica tions at the University of Minnesota. It was part of the Special Year on Emerging Applications of Prob ability program put together by an organiz ing committee chaired by J. Michael Steele. The invited speakers represented a broad interdisciplinary spectrum including mathematics, statistics, physics, geophysics, astrophysics, atmo spheric physics, fluid mechanics, seismology, and oceanography. The com mon underlying theme was stochastic modeling of geophysical phenomena and papers appearing in this volume reflect a number of research directions that are currently pursued in these areas.

Codes, Systems, and Graphical Models

Codes, Systems, and Graphical Models

Author: Brian Marcus

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 520

ISBN-13: 1461301653

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Coding theory, system theory, and symbolic dynamics have much in common. A major new theme in this area of research is that of codes and systems based on graphical models. This volume contains survey and research articles from leading researchers at the interface of these subjects.


Book Synopsis Codes, Systems, and Graphical Models by : Brian Marcus

Download or read book Codes, Systems, and Graphical Models written by Brian Marcus and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coding theory, system theory, and symbolic dynamics have much in common. A major new theme in this area of research is that of codes and systems based on graphical models. This volume contains survey and research articles from leading researchers at the interface of these subjects.