DocumentCode
971053
Title
Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators
Author
Campbell, Shannon ; Wang, DeLiang
Author_Institution
Dept. of Phys., Ohio State Univ., Columbus, OH, USA
Volume
7
Issue
3
fYear
1996
fDate
5/1/1996 12:00:00 AM
Firstpage
541
Lastpage
554
Abstract
A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation
Keywords
Hebbian learning; digital simulation; feedback; image segmentation; neural nets; oscillators; piecewise-linear techniques; synchronisation; 2D matrix; Gestalt principles; Hebbian rule; component spatial relationships preservation; computer simulation; coupling strengths; desynchronization; emergent properties; feature grouping; feedback; figure/ground segregation; formal analysis; global separator; local connections; locally coupled Wilson-Cowan oscillator network; oscillator entrainment; oscillatory correlation; pattern segmentation; piecewise linear approximation; synchronization; Computer simulation; Feedback; Helium; Intelligent networks; Layout; Linear approximation; Local oscillators; Neurodynamics; Optical wavelength conversion; Particle separators;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.501714
Filename
501714
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