Foundations of Quantization for Probability Distributions

  • Authors
  • Siegfried Graf
  • Harald Luschgy

Part of the Lecture Notes in Mathematics book series (LNM, volume 1730)

Table of contents

  1. Front Matter
    Pages i-x
  2. Siegfried Graf, Harald Luschgy
    Pages 1-5
  3. Siegfried Graf, Harald Luschgy
    Pages 77-154
  4. Siegfried Graf, Harald Luschgy
    Pages 155-207
  5. Back Matter
    Pages 209-230

About this book

Introduction

Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.

Keywords

Cluster analysis Measure Pattern Recognition Probability distribution Probability theory data compression image processing information information theory operations research sets

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0103945
  • Copyright Information Springer-Verlag Berlin Heidelberg 2000
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-67394-1
  • Online ISBN 978-3-540-45577-6
  • Series Print ISSN 0075-8434
  • Series Online ISSN 1617-9692
  • About this book