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08 Jul 2018
Marcos Valle Keynote talk (FUZZ-IEEE) at WCCI 2018
Abstract:"Associative memories are models inspired by the human brain ability to recall information by association. We speak of a fuzzy associative memory when the associative memory is designed for the storage and recall of fuzzy sets on a finite universe of discourse. Apart from the biological motivation, a fuzzy associative memory is a continuous fuzzy system that maps close input to close output.
We shall begin this talk by reviewing the matrix-based fuzzy associative memories, which are closely related to the compositional rule of inference. Examples of matrix-based fuzzy associative memories include the famous models of Kosko and the implicative fuzzy associative memories. We point out that many matrix-based fuzzy associative memories can be embedded into the general class of fuzzy morphological associative memories. In the light of this remark, we review some key concepts of mathematical morphology, a theory widely used for image processing and analysis. Particular attention is given to auto-associative fuzzy morphological memories, in which we provide theoretical results concerning the storage capacity, noise tolerance, and fixed points. Afterward, we shall address recent advances on fuzzy associative memories. Furthermore, we shall present some applications of fuzzy associative memories for time series prediction, pattern recognition, and computer vision.
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Abstract:"Associative memories are models inspired by the human brain ability to recall information by association. We speak of a fuzzy associative memory when the associative memory is designed for the storage and recall of fuzzy sets on a finite universe of discourse. Apart from the biological motivation, a fuzzy associative memory is a continuous fuzzy system that maps close input to close output.
We shall begin this talk by reviewing the matrix-based fuzzy associative memories, which are closely related to the compositional rule of inference. Examples of matrix-based fuzzy associative memories include the famous models of Kosko and the implicative fuzzy associative memories. We point out that many matrix-based fuzzy associative memories can be embedded into the general class of fuzzy morphological associative memories. In the light of this remark, we review some key concepts of mathematical morphology, a theory widely used for image processing and analysis. Particular attention is given to auto-associative fuzzy morphological memories, in which we provide theoretical results concerning the storage capacity, noise tolerance, and fixed points. Afterward, we shall address recent advances on fuzzy associative memories. Furthermore, we shall present some applications of fuzzy associative memories for time series prediction, pattern recognition, and computer vision.
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