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Fuzzy Kernel Associative Memories with Application in Classification

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Fuzzy Information Processing (NAFIPS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 831))

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Abstract

In this paper we introduce the class of fuzzy kernel associative memories (fuzzy KAMs). Fuzzy KAMs are derived from single-step generalized exponential bidirectional fuzzy associative memories by interpreting the exponential of a fuzzy similarity measure as a kernel function. The output of a fuzzy KAM is obtained by summing the desired responses weighted by a normalized evaluation of the kernel function. Furthermore, in this paper we propose to estimate the parameter of a fuzzy KAM by maximizing the entropy of the model. We also present two approaches for pattern classification using fuzzy KAMs. Computational experiments reveal that fuzzy KAM-based classifiers are competitive with well-known classifiers from the literature.

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Acknowledgment

This work was supported in part by FAPESP and CNPq under grants nos 2015/00745-1 and 310118/2017-4, respectively.

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Authors and Affiliations

  1. Department of Applied Mathematics, University of Campinas, Campinas, São Paulo, 13081-970, Brazil

    Aline Cristina de Souza & Marcos Eduardo Valle

Authors
  1. Aline Cristina de Souza
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  2. Marcos Eduardo Valle
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Corresponding author

Correspondence to Marcos Eduardo Valle .

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Editors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Guilherme A. Barreto

  2. Department of Statistics & Applied Mathematics, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Ricardo Coelho

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de Souza, A.C., Valle, M.E. (2018). Fuzzy Kernel Associative Memories with Application in Classification. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_25

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  • DOI: https://doi.org/10.1007/978-3-319-95312-0_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95311-3

  • Online ISBN: 978-3-319-95312-0

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