A Geometrical Strategy of Constructive Initial Neural Networks
神经网络设计的特征空间序贯划分算法

A geometrical strategy for constructive neural networks is proposed in the paper. Firstly it can acquire quickly initial input weight parameters and topolgy by sequentially partioning feature space with the presented geometrical method. Secondly with SVD,its initial output weights are obtained very quickly. Finally these weights are retuned with BP algorithms. Its distinctive features are that it can construct quickly an initial neural networks using geometrical method other than backpropagation algorithms so that overtraining and undertraining are avoided automatically,and experimentally it performs better on two-spiral classification than Cascade-Correlation Algorithm.