Geodesic
An oscillatory network model with controllable synchronization and neuromorphic dynamical method of information processing
Matematičeskoe modelirovanie, Tome 29 (2017) no. 1, pp. 95-108

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Spatially two-dimensional oscillatory neural network model with inhomogeneous modifiable oscillatory coupling has been designed and adaptive dynamical method of brightness image segmentation (reconstruction) based on self-organized cluster synchronization in the oscillatory network has been developed. The method imitates the known dynamical binding phenomenon that is presumably used by a number of brain neural structures during their performance. The oscillatory-network approach demonstrates the following capabilities: 1) high quality segmentation of real grey-level and color images; 2) selective image segmentation (exclusion of unnecessary information); 3) solution of a problem of visual scene segmentation — the problem of successive selection of all spatially separated image fragments of almost equal brightness.
Keywords: oscillatory networks, synchronization, neuromorphic methods of information processing, dynamical binding, vision scene analysis.
Mots-clés : image segmentation 
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     author = {E. S. Grichuk and M. G. Kuzmina and E. A. Manykin},
     title = {An oscillatory network model with controllable synchronization and neuromorphic dynamical method of information processing},
     journal = {Matemati\v{c}eskoe modelirovanie},
     pages = {95--108},
     publisher = {mathdoc},
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     number = {1},
     year = {2017},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MM_2017_29_1_a6/}
}
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E. S. Grichuk; M. G. Kuzmina; E. A. Manykin. An oscillatory network model with controllable synchronization and neuromorphic dynamical method of information processing. Matematičeskoe modelirovanie, Tome 29 (2017) no. 1, pp. 95-108. http://geodesic.mathdoc.fr/item/MM_2017_29_1_a6/