Efficient training for dendrite morphological neural networks
An efficient training algorithm for a dendrite morphological neural network. Convergence in a finite number of steps. Perfect classification of the training data. No overlap between hyper-cubes with distinct class labels. The algorithm can be applied to classification problems of p classes and n attributes.
efficient training dendrite morphological neural network classification pattern recognition