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Image Models (and their Speech Model Cousins)

  • Conference proceedings
  • © 1996

Overview

Editors:
  1. Stephen E. Levinson

    1. Bell Laboratories, Murray Hill, USA

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  2. Larry Shepp

    1. Bell Laboratories, Murray Hill, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: The IMA Volumes in Mathematics and its Applications (IMA, volume 80)

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Table of contents (11 papers)

  1. Front Matter

    Pages i-ix
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  2. Iterative Reconstruction Algorithms Based on Cross-Entropy Minimization

    • Charles Byrne
    Pages 1-11

  3. Stop Consonants Discrimination and Clustering Using Nonlinear Transformations and Wavelets

    • Basilis Gidas, Alejandro Murua
    Pages 13-62

  4. Maximum a Posteriori Image Reconstruction from Projections

    • Gabor T. Herman, Michael Chan, Yair Censor, Emanuel Levitan, Robert M. Lewitt, T. K. Narayan
    Pages 63-89

  5. Direct Parsing of Text

    • F. Jelinek
    Pages 91-105

  6. Hierarchical Modelling for Microstructure of Certain Brittle Materials

    • Chuanshu Ji
    Pages 107-114

  7. Hidden Markov Models Estimation Via the Most Informative Stopping Times for the Viterbi Algorithm

    • Joseph A. Kogan
    Pages 115-130

  8. Constrained Stochastic Language Models

    • Kevin E. Mark, Michael I. Miller, Ulf Grenander
    Pages 131-140

  9. Recovering DNA Sequences from Electrophoresis Data

    • David O. Nelson, Terence P. Speed
    Pages 141-152

  10. Image and Speech and EM

    • Larry Shepp
    Pages 153-159

  11. Non-Stationary Hidden Markov Models for Speech Recognition

    • Don X. Sun, Li Deng
    Pages 161-182

  12. Applications of the EM Algorithm to Linear Inverse Problems with Positivity Constraints

    • Y. Vardi
    Pages 183-198

  13. Back Matter

    Pages 199-204
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Keywords

About this book

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.

Editors and Affiliations

  • Bell Laboratories, Murray Hill, USA

    Stephen E. Levinson, Larry Shepp

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