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• W2149618784 abstract "Autoassociative fuzzy implicative memories (AFIMs) are models that exhibit optimal absolute storage capacity and an ex- cellent tolerance with respect to incomplete or eroded patterns. Thus, they can be effectively used for the reconstruction of gray-scale im- ages. In practice, however, applications of AFIMs are confined to images of small size due to computational limitations. This paper introduces a class of sparsely connected AFIMs (SCAFIMs) that cir- cumvent this computational overhead and, therefore, can be used for the reconstruction of large images. We show that SCAFIMs exhibit optimal absolute storage capacity and tolerance with respect to in- complete or eroded patterns. Furthermore, we compare the perfor- mance of SCAFIMs with their corresponding fully connected AFIM both theoretically and by means of computational experiments. Keywords— Fuzzy associative memory, reconstruction of large gray-scale images, sparse encoding, storage capacity, tolerance with respect to noise." @default.
• W2149618784 created "2016-06-24" @default.
• W2149618784 creator A5012009095 @default.
• W2149618784 date "2009-01-01" @default.
• W2149618784 modified "2023-09-26" @default.
• W2149618784 title "Sparsely Connected Autoassociative Fuzzy Implicative Memories for the Reconstruction of Large Gray-Scale Images" @default.
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