Description

Book Synopsis

Nonlinear Digital Filtering with Python: An Introduction discusses important structural filter classes including the median filter and a number of its extensions (e.g., weighted and recursive median filters), and Volterra filters based on polynomial nonlinearities. Adopting both structural and behavioral approaches in characterizing and designing nonlinear digital filters, this book:

  • Begins with an expedient introduction to programming in the free, open-source computing environment of Python
  • Uses results from algebra and the theory of functional equations to construct and characterize behaviorally defined nonlinear filter classes
  • Analyzes the impact of a range of useful interconnection strategies on filter behavior, providing Python implementations of the presented filters and interconnection strategies
  • Proposes practical, bottom-up strategies for designing more complex and capable filters from simpler components in a way that preserves the

    Trade Review

    "The authors bring the reader from the consolidated world of linear filters into the variegate universe of nonlinear filters, and show how the main subclasses of digital nonlinear filters can be described on the basis of their structural and/or behavioral characteristics. This approach is complemented by the use of a free, open-source computing environment—Python—for the implementation of the nonlinear digital filters presented in each chapter."
    —Giovanni L. Sicuranza, University of Trieste, Italy



    Table of Contents

    Introduction. Python. Linear and Volterra Filters. Median Filters and Some Extensions. Forms of Nonlinear Behavior. Composite Structures: Bottom-Up Design. Recursive Structures and Stability.

Nonlinear Digital Filtering with Python

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A Hardback by Ronald K. Pearson, Moncef Gabbouj

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    View other formats and editions of Nonlinear Digital Filtering with Python by Ronald K. Pearson

    Publisher: Taylor & Francis Inc
    Publication Date: 25/09/2015
    ISBN13: 9781498714112, 978-1498714112
    ISBN10: 1498714110
    Also in:
    Electrical engineering Environmental science, engineering and technology WAP (wireless) technology

    Description

    Book Synopsis

    Nonlinear Digital Filtering with Python: An Introduction discusses important structural filter classes including the median filter and a number of its extensions (e.g., weighted and recursive median filters), and Volterra filters based on polynomial nonlinearities. Adopting both structural and behavioral approaches in characterizing and designing nonlinear digital filters, this book:

    • Begins with an expedient introduction to programming in the free, open-source computing environment of Python
    • Uses results from algebra and the theory of functional equations to construct and characterize behaviorally defined nonlinear filter classes
    • Analyzes the impact of a range of useful interconnection strategies on filter behavior, providing Python implementations of the presented filters and interconnection strategies
    • Proposes practical, bottom-up strategies for designing more complex and capable filters from simpler components in a way that preserves the

      Trade Review

      "The authors bring the reader from the consolidated world of linear filters into the variegate universe of nonlinear filters, and show how the main subclasses of digital nonlinear filters can be described on the basis of their structural and/or behavioral characteristics. This approach is complemented by the use of a free, open-source computing environment—Python—for the implementation of the nonlinear digital filters presented in each chapter."
      —Giovanni L. Sicuranza, University of Trieste, Italy



      Table of Contents

      Introduction. Python. Linear and Volterra Filters. Median Filters and Some Extensions. Forms of Nonlinear Behavior. Composite Structures: Bottom-Up Design. Recursive Structures and Stability.

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