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Proceedings Paper

DIGNET: a self-organizing neural network for automatic pattern recognition, classification, and data fusion
Author(s): Stelios C.A. Thomopoulos; Dimitrios K. Bougoulias
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Paper Abstract

DIGNET is a self-organizing artificial neural network (ANN) that exhibits deterministically reliable behavior to noise interference, when the noise does not exceed a pre-specified level of tolerance. The complexity of the proposed ANN, in terms of neuron requirements versus stored patterns, increases linearly with the number of stored patterns and their dimensionality. The self-organization of the DIGNET is based on the idea of competitive generation and elimination of attraction wells in the pattern space. DIGNET is used for pattern recognition and classification. Analytical and numerical results are included.

Paper Details

Date Published: 30 April 1992
PDF: 18 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57947
Show Author Affiliations
Stelios C.A. Thomopoulos, The Pennsylvania State Univ. (United States)
Dimitrios K. Bougoulias, Univ. of Southern Illinois (United States)


Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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