Gray-Scale Morphological Associative Memories  

Oleh:

Sussner, P. ; Valle, M. E.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 17 no. 3 (May 2006), page 559-570.
Topik: screen memories; gray - scale; morphological; memories

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Neural models of associative memories are usually concerned with the storage and the retrieval of binary or bipolar patterns. Thus far, the emphasis in research on morphological associative memory systems has been on binary models, although a number of notable features of autoassociative morphological memories (AMM s) such as optimal absolute storage capacity and one - step convergence have been shown to hold in the general, gray - scale setting. In this paper, we make extensive use of minimax algebra to analyze gray - scale autoassociative morphological memories. Specifically, we provide a complete characterization of the fixed points and basins of attractions which allows us to describe the storage and recall mechanisms of gray - scale AMM s. Computer simulations using gray - scale images illustrate our rigorous mathematical results on the storage capacity and the noise tolerance of gray -scale morphological associative memories (MAM s). Finally, we introduce a modified gray - scale AMM model that yields a fixed point which is closest to the input pattern with respect to the Chebyshev distance and show how gray -scale AMM s can be used as classifiers.

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