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JOURNALS // Matematicheskoe modelirovanie // Archive

Matem. Mod., 2017 Volume 29, Number 1, Pages 95–108 (Mi mm3809)

An oscillatory network model with controllable synchronization and neuromorphic dynamical method of information processing

E. S. Grichuka, M. G. Kuzminab, E. A. Manykina

a National Research Center "Kurchatov Institute", Moscow
b Keldysh Institute of Applied Mathematics RAS, Moscow

Abstract: 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, image segmentation, vision scene analysis.

Received: 21.12.2015


 English version:
Mathematical Models and Computer Simulations, 2017, 9:4, 511–520

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© Steklov Math. Inst. of RAS, 2024