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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2012: Hybrid Artificial Intelligent Systems pp 479–490Cite as

Fuzzy Associative Memories Based on Subsethood and Similarity Measures with Applications to Speaker Identification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7209))

Abstract

Recently, we presented a non-distributive fuzzy associative memory (FAM) called the Kosko subsethood FAM, for short KS-FAM. This model can be classified as a morphological neural network because it is based on computing the degree of fuzzy inclusion or subsethood of patterns and this operation can be considered an erosion in fuzzy mathematical morphology. In this paper, we introduce a whole range of extensions of the KS-FAM called S-FAMs, dual S-FAMs, and SM-FAMs. Here, the acronyms S-FAM and SM-FAM stand for respectively subsethood FAM and similarity measure FAM. The new models share some properties with the KS-FAM such as unlimited absolute storage capacity and a small number of spurious memories. The paper finishes some experimental results concerning the problem of text-independent speaker identification. For comparative purposes, we included the recognition rates obtained by some well-known classifiers from the literature.

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Author information

Authors and Affiliations

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

    Estevão Esmi, Peter Sussner & Laécio Barros

  2. Department of Mathematics, University of Londrina, Londrina, Paraná, Brazil

    Marcos Eduardo Valle

  3. Department of Computer Science, University of Londrina, Londrina, Paraná, Brazil

    Fábio Sakuray

Authors
  1. Estevão Esmi
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  2. Peter Sussner
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  3. Marcos Eduardo Valle
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  4. Fábio Sakuray
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  5. Laécio Barros
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Editor information

Editors and Affiliations

  1. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VŠB-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs Machine Intelligence Research Labs(MIR Labs),, Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, 120-749, Sudaemoon-ku, Seoul, Korea

    Sung-Bae Cho

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© 2012 Springer-Verlag Berlin Heidelberg

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Esmi, E., Sussner, P., Valle, M.E., Sakuray, F., Barros, L. (2012). Fuzzy Associative Memories Based on Subsethood and Similarity Measures with Applications to Speaker Identification. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28931-6_46

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  • DOI: https://doi.org/10.1007/978-3-642-28931-6_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28930-9

  • Online ISBN: 978-3-642-28931-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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