DIGNET: A self-organizing neural network for automatic pattern recognition and classification
Stelios C. A. Thomopoulos, D.K. Bougoulias · 1991
A self-organizing artificial neural network (ANN) that exhibits deterministically reliable behavior to noise interference when the noise does not exceed a specified level of tolerance is presented. 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 proposed ANN is based on the idea of competitive generation and elimination of attraction wells in the pattern space. The same neural network can be used both for pattern recognition and classification. The ANN has been tested successfully with pattern and signal recognition and classification paradigms.>