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Proceedings Paper

Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation
Author(s): DeLiang Wang; David Terman
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Paper Abstract

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

Paper Details

Date Published: 31 January 1995
PDF: 8 pages
Proc. SPIE 2368, 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities, (31 January 1995); doi: 10.1117/12.200790
Show Author Affiliations
DeLiang Wang, The Ohio State Univ. (United States)
David Terman, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 2368:
23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities
Peter J. Costianes, Editor(s)

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