A New Competitive Neural Network With Self-Adaptive Structure

A traditional competitive neural network(CNN)has the shortcomings that the output neuron number should be determined in advance for cluster analysis and the clustering result depends heavily on the selection of the initial weights. A new CNN with self adaptive structure is presented, which adjusts the output neuron number according to the modification Huber(MH) mark of the clustering result. The numerical experiment results show that the new CNN can provide excellent cluster analysis results.\;