Skip to main content
SpringerLink
Log in

Information Loss in Deterministic Signal Processing Systems

  • Book
  • © 2018

Overview

Authors:
  1. Bernhard C. Geiger

    1. Institute for Communications Engineering, Technical University of Munich, Munich, Germany

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Gernot Kubin

    1. Signal Processing and Speech Communication Lab, Graz University of Technology, Graz, Austria

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Presents a definition of information loss for signal processing systems which is the basis of an information-theoretic systems theory
  • 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.
  • Highlights differences and similarities between design principles based on information-theoretic quantities and those based on energetic measures, such as the mean-squared error
  • Includes supplementary material: sn.pub/extras

Part of the book series: Understanding Complex Systems (UCS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Introduction

    • Bernhard C. Geiger, Gernot Kubin
    Pages 1-14

  3. Random Variables

    1. Front Matter

      Pages 15-15
      Download chapter PDF

    2. Piecewise Bijective Functions and Continuous Inputs

      • Bernhard C. Geiger, Gernot Kubin
      Pages 17-34

    3. General Input Distributions

      • Bernhard C. Geiger, Gernot Kubin
      Pages 35-42

    4. Dimensionality-Reducing Functions

      • Bernhard C. Geiger, Gernot Kubin
      Pages 43-72

    5. Relevant Information Loss

      • Bernhard C. Geiger, Gernot Kubin
      Pages 73-89

  4. Stationary Stochastic Processes

    1. Front Matter

      Pages 91-91
      Download chapter PDF

    2. Discrete-Valued Processes

      • Bernhard C. Geiger, Gernot Kubin
      Pages 93-103

    3. Piecewise Bijective Functions and Continuous Inputs

      • Bernhard C. Geiger, Gernot Kubin
      Pages 105-113

    4. Dimensionality-Reducing Functions

      • Bernhard C. Geiger, Gernot Kubin
      Pages 115-125

    5. Relevant Information Loss Rate

      • Bernhard C. Geiger, Gernot Kubin
      Pages 127-136

    6. Conclusion and Outlook

      • Bernhard C. Geiger, Gernot Kubin
      Pages 137-139

  5. Back Matter

    Pages 141-145
    Download chapter PDF
Back to top

Keywords

About this book

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.

Reviews





Authors and Affiliations

  • Institute for Communications Engineering, Technical University of Munich, Munich, Germany

    Bernhard C. Geiger

  • Signal Processing and Speech Communication Lab, Graz University of Technology, Graz, Austria

    Gernot Kubin

Bibliographic Information

  • Book Title: Information Loss in Deterministic Signal Processing Systems

  • Authors: Bernhard C. Geiger, Gernot Kubin

  • Series Title: Understanding Complex Systems

  • DOI: https://doi.org/10.1007/978-3-319-59533-7

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Hardcover ISBN: 978-3-319-59532-0Published: 10 July 2017

  • Softcover ISBN: 978-3-319-86645-1Published: 04 August 2018

  • eBook ISBN: 978-3-319-59533-7Published: 02 July 2017

  • Series ISSN: 1860-0832

  • Series E-ISSN: 1860-0840

  • Edition Number: 1

  • Number of Pages: XIII, 145

  • Number of Illustrations: 7 b/w illustrations, 9 illustrations in colour

  • Topics: Complexity, Signal, Image and Speech Processing, Complex Systems

Publish with us

Policies and ethics

Back to top

Search

Navigation