Last edited by Daile
Friday, May 8, 2020 | History

5 edition of Nonlinear digital filters found in the catalog.

Nonlinear digital filters

principles and applications

by I. Pitas

  • 6 Want to read
  • 15 Currently reading

Published by Kluwer Academic Publishers in Boston .
Written in English

    Subjects:
  • Electric filters, Digital.

  • Edition Notes

    Includes bibliographical references.

    Statementby I. Pitas and A.N. Venetsanopoulos.
    SeriesThe Kluwer international series in engineering and computer science.
    ContributionsVenetsanopoulos, A. N. 1941-
    Classifications
    LC ClassificationsTK7872.F5 P58 1990
    The Physical Object
    Paginationxiv, 392 p. :
    Number of Pages392
    ID Numbers
    Open LibraryOL2204821M
    ISBN 100792390490
    LC Control Number89026769

    A memoryless nonlinearity followed by an LTI filter can similarly be characterized by a stack of impulse-responses indexed by amplitude (look up dynamic convolution on the Web). One often-used tool for nonlinear systems analysis is Volterra series. A Volterra series expansion represents a nonlinear system as a sum of iterated convolutions. DIGITAL FILTERS Chapter Introduction to Digital Filters Chapter Examples of Linear and Nonlinear Systems 94 Special Properties of Linearity 96 Superposition: the Foundation of DSP 98 example of this than Digital Signal Processing. In the early s, DSP was taught as a graduate level course in electrical engineering. File Size: 46KB.

    An Introduction to Digital Filters AN Rev Page 3 of 10 January filter except in their relation to the sampling frequency. This is because the impulse response is generated as a function of z-1, the sample interval (the time between samples). For a smaller shape factor, the order of the filter and the number ofFile Size: KB. C. A. Bouman: Digital Image Processing - January 7, 1 Nonlinear Filtering • Linear filters – Tend to blur edges and other image detail. – Perform poorly with non-Gaussian noise. – Result from Gaussian image and noise assumptions. – Images are not Gaussian. • Nonlinear filter – Can preserve edgesFile Size: 73KB.

    Binary Polynomial Transforms and Non-Linear Digital Filters - CRC Press Book This work offers a unified presentation of the theory of binary polynomial transforms and details their numerous applications in nonlinear signal processing. The new structure reduces the computational cost of the nonlinear digital Moog filter by using a single nonlinearity in the feedback loop instead of four nonlinear functions inside filter : Risto Holopainen.


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Nonlinear digital filters by I. Pitas Download PDF EPUB FB2

There are numerous examples from image processing which show the effects of the various non-linear digital filters visually. Although the book is biased to filtering problem in image processing, I've used the sections on M-estimators, L-estimators, R-estimators, median filters, and the variants of order statistic filters in many problems not related to by: Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters.

It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time systems, such as sigma delta modulators, digital phase Cited by: 4.

Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters. It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time systems, such as sigma delta modulators, digital phase.

Numerous authors have considered deterministic and statistical approaches for the study of passive, active, digital, multidimen­ sional, and adaptive filters.

Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now : Springer US.

Nonlinear Digital Filters. The function of a filter is to transform a signal into another one more suit able for a given purpose. As such, filters find applications in telecommunica tions, radar, sonar, remote sensing, geophysical signal processing, image pro cessing, and computer s: 1.

Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided Nonlinear digital filters book operating nonlinear digital filters. It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time Brand: Elsevier Science.

Numerous authors have considered deterministic and statistical approaches for the study of passive, active, digital, multidimen sional, and adaptive filters. Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now available.

This book provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters.

It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time systems, such as sigma delta modulators, digital phase lock loops.

Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now available. Our research interests in this area created opportunity for cooperation and co­ authored publications during.

About the Book. Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters. It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete.

Book Description. 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 ng both structural and behavioral approaches in characterizing and designing nonlinear digital filters.

2 Chapter 5 Digital Filters Introduction Filters are widely employed in signal processing and communication systems in applications such as channel equalization, noise reduction, radar, audio processing, video processing, biomedical signal processing, and analysis of economic and financial data.

For example in a radio receiver band-pass. This book provides an easy to understand overview of Nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating Nonlinear digital filters. It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other Nonlinear discrete-time systems, such as sigma delta modulators, digital phase lock.

Note: If you're looking for a free download links of Nonlinear Digital Filters: Principles and Applications (The Springer International Series in Engineering and Computer Science) Pdf, epub, docx and torrent then this site is not for you. only do ebook promotions online and we does not distribute any free download of ebook on this site.

In signal processing, a nonlinear (or non-linear) filter is a filter whose output is not a linear function of its input. That is, if the filter outputs signals R and S for two input signals r and s separately, but does not always output αR + βS when the input is a linear combination αr + βs.

Nonlinear Digital Filters | The function of a filter is to transform a signal into another one more suit- able for a given purpose. As such, filters find applications in telecommunica- tions, radar, sonar, remote sensing, geophysical signal processing, image pro- cessing, and computer vision.

Fundamentals of Nonlinear Digital Filtering is the first book of its kind, presenting and evaluating current methods and applications in nonlinear digital filtering. Written for professors, researchers, and application engineers, as well as for serious students of signal processing, this is the only book available that functions as both a.

This chapter presents the coordinate logic (CL) filters, a new family of nonlinear digital filters based on the execution of coordinate logic operations.

Image processing and analysis using CL filters is achieved by executing direct coordinate logic operations among the pixels of. Nonlinear Digital Filters: Principles and Applications (The Springer International Series in Engineering and Computer Science) Pdf, Download.

This book is a revision of Nonlinear Filters: Estimation and Applications, (Lecture Notes in Economics and Mathematical Systems, No), which was published from Springer-Verlag in Compared with the first edition, I have made a substantial revision in the second Size: KB.

It gives practical, 'real-world' applications of nonlinear digital filters and contains many examples. The book is ideal for professional engineers working with signal processing applications, as well as advanced undergraduates and graduates conducting a nonlinear filter analysis project.

(source: Nielsen Book Data).Get this from a library! Nonlinear digital filters: analysis and applications. [Wing-Kuen Ling] -- "This book provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters.

It .Design of FIR Filters An FIR lter of length M is an LTI system with the following difference equation1: y[n] = MX 1 k=0 bk x[n k]: Note that the book changes the role of M here.

Earlier, when discussing rational system functions, M was the number of zeros. Now M is the number of finonzerofl elements of h[n], which corresponds to at most M 1.