Nonlinear Digital Filtering with Python: An Introduction, 1st Edition – FULL INSTANT DOWNLOAD | PDF DOCX EPUB

Name: Nonlinear Digital Filtering with Python: An Introduction
Edition: 1st Edition
ISBN-13: 9781498714112
ISBN-10: 1498714110
Addition ISBN: 9781315214269, 9781351830157, 9781351821469, 1498714137, 9781498714136
Author(s): Ronald K. Pearson; Moncef Gabbouj, Publisher: CRC Press, Copyright: 2016
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 key properties of these components Illustrates the behavioral consequences of allowing recursive (i.e., feedback) interconnections in nonlinear digital filters while highlighting a challenging but promising research frontier Nonlinear Digital Filtering with Python: An Introduction supplies essential knowledge useful for developing and implementing data cleaning filters for dynamic data analysis and time-series modeling.