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


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

A spatially two-dimensional oscillatory neural network model with inhomogeneous modifiable oscillatory coupling is designed and an adaptive dynamical method of brightness image segmentation (image reconstruction) based on self-organized cluster synchronization in the oscillatory network is developed. The method imitates the known phenomenon of dynamical binding via synchronization that is presumably used by a number of the brain neural structures in their work. 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 the simplest problem of object selection in a visual scene—the problem of the successive selection of all spatially separated image fragments of almost equal brightness.

作者简介

E. Grichuk

National Research Center Kurchatov Institute

Email: mg.kuzmina@gmail.com
俄罗斯联邦, Moscow

M. Kuzmina

Keldysh Institute of Applied Mathematics

编辑信件的主要联系方式.
Email: mg.kuzmina@gmail.com
俄罗斯联邦, Moscow

E. Manykin

National Research Center Kurchatov Institute

Email: mg.kuzmina@gmail.com
俄罗斯联邦, Moscow


版权所有 © Pleiades Publishing, Ltd., 2017
##common.cookie##