Storage of fuzzy information in continuous classifying associative memories

  • Authors:

  • Antonio B. Bailón;Miguel Delgado;Waldo Fajardo

  • Affiliations:

  • Dpto. Lenguajes y Computación, Universidad de Almería, La Cañada de San Urbano 04120 Almería (Spain);Dpto. Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, C/Daniel Saucedo Aranda s/n 18071 Granada (Spain);Dpto. Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, C/Daniel Saucedo Aranda s/n 18071 Granada (Spain)

  • Venue:
  • Enterprise information systems IV
  • Year:
  • 2003

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Abstract

In this paper, we analyze the use of the Continuous Classifying Associative Memory (CCLAM) to store imprecise information expressed with linguistic terms. Freedom in the choice of the functions which control the operation of the CCLAM equip this memory with the capacity to adapt to different information storage and recovery needs. We begin with the problem of storing linguistic terms by memorizing the patterns formed by the degrees of compatibility with these terms. This will allow the use of CCLAM to compute the firing strength of rules whose antecedent is expressed in linguistic terms. After that, the problem of storing Mamdani and TSK rules is discussed.