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Improving Approximation Properties of Fuzzy Transform Through Non-uniform Partitions

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Fuzzy Logic and Soft Computing Applications (WILF 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10147))

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Abstract

Function reconstruction is one of the valuable properties of the Fuzzy Transform and its inverse. The quality of reconstruction depends on how dense the fuzzy partition of the function domain is. However, the partition should be denser where the function exhibits faster variations, while the partition can be less dense where the function is moving slowly. In this paper, we investigate the possibility of having non-uniform fuzzy partitions, in order to better accommodate a different behavior of function across its domain.

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze Aziendali - Management & Innovation Systems (DISA-MIS), Università degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Vincenzo Loia

  2. CORISA, Dipartimento di Ingegneria dell’Informazione ed Elettrica e Matematica Applicata (DIEM), Università degli Studi di Salerno, via Giovanni Paolo II, 132, 84084, Fisciano, Italy

    Stefania Tomasiello

  3. Dipartimento di Ingegneria (DING), Università degli Studi del Sannio, Piazza Roma 21, 82100, Benevento, Italy

    Luigi Troiano

Authors
  1. Vincenzo Loia
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  2. Stefania Tomasiello
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  3. Luigi Troiano
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Corresponding author

Correspondence to Luigi Troiano .

Editor information

Editors and Affiliations

  1. University of Naples “Parthenope”, Naples, Italy

    Alfredo Petrosino

  2. University of Salerno, Fisciano, (Salerno), Italy

    Vincenzo Loia

  3. University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

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Loia, V., Tomasiello, S., Troiano, L. (2017). Improving Approximation Properties of Fuzzy Transform Through Non-uniform Partitions. In: Petrosino, A., Loia, V., Pedrycz, W. (eds) Fuzzy Logic and Soft Computing Applications. WILF 2016. Lecture Notes in Computer Science(), vol 10147. Springer, Cham. https://doi.org/10.1007/978-3-319-52962-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-52962-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52961-5

  • Online ISBN: 978-3-319-52962-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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