Classification Algorithm of Neural Network Based on Axon Signal Theory

With reference to the theory that only a part of signal from brain cells can reach pallium put forward by Raju Metherate, and the theory that axon signal strength is reduced with distance increment from main body of neural cells raised by Stephen R. Williams, axon signal theory-based clustering algorithm of neural network is presented in this paper. This algorithm processes equivalent to and even higher clustering accuracy than traditional competitive neural network in space with higher dimension. The further analysis of training result of neural network can be seen as a basis of space dimension reduction and primary component analysis, and self-organization relationships of categories can thus be yielded by weights of neural neurons in competitive layers. Finally the effectiveness of this algorithm is proved in experiments.