Title :
DIGNET: a self-organizing neural network for automatic pattern recognition and classification
Author :
Thomopoulos, Stelios C A ; Bougoulias, Dimitrios K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
The authors present 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. The complexity of the proposed ANN, called DIGNET, in terms of neuron requirements versus stored patterns, increases linearly with the number of stored patterns and their dimensionality. The self-organization of DIGNET is based on the idea of competitive generation and elimination of attraction wells in the pattern space. The same neural network can be used for both pattern recognition and classification
Keywords :
interference (signal); neural nets; noise; pattern recognition; self-organising storage; DIGNET; artificial neural network; attraction wells; automatic pattern recognition; classification; competitive generation; deterministically reliable behavior; neuron requirements; noise interference; self-organizing neural network; Artificial neural networks; Automatic control; Interference; Laboratories; Neural networks; Neurons; Noise level; Pattern recognition; Signal detection; Vectors;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261437