Information Loss in Deterministic Signal Processing Systems

  • Bernhard C. Geiger
  • Gernot Kubin

Part of the Understanding Complex Systems book series (UCS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Bernhard C. Geiger, Gernot Kubin
    Pages 1-14
  3. Random Variables

    1. Front Matter
      Pages 15-15
    2. Bernhard C. Geiger, Gernot Kubin
      Pages 17-34
    3. Bernhard C. Geiger, Gernot Kubin
      Pages 35-42
    4. Bernhard C. Geiger, Gernot Kubin
      Pages 43-72
    5. Bernhard C. Geiger, Gernot Kubin
      Pages 73-89
  4. Stationary Stochastic Processes

    1. Front Matter
      Pages 91-91
    2. Bernhard C. Geiger, Gernot Kubin
      Pages 93-103
    3. Bernhard C. Geiger, Gernot Kubin
      Pages 105-113
    4. Bernhard C. Geiger, Gernot Kubin
      Pages 115-125
    5. Bernhard C. Geiger, Gernot Kubin
      Pages 127-136
    6. Bernhard C. Geiger, Gernot Kubin
      Pages 137-139
  5. Back Matter
    Pages 141-145

About this book

Introduction

This book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer’s toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory—data processing inequality—states that deterministic processing always involves information loss. 

These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order
statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.


Keywords

Linear Filters System Theory Multirate Systems Information Processing Information Theory Polynomials Principal Components Analysis

Authors and affiliations

  • Bernhard C. Geiger
    • 1
  • Gernot Kubin
    • 2
  1. 1.Institute for Communications EngineeringTechnical University of MunichMunichGermany
  2. 2.Signal Processing and Speech Communication LabGraz University of TechnologyGrazAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-59533-7
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-59532-0
  • Online ISBN 978-3-319-59533-7
  • Series Print ISSN 1860-0832
  • Series Online ISSN 1860-0840
  • About this book

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