The invention provides a self-organizing neural network topology preservation reinforcing method based on deep learning. The method is used for settling a technical problem of requirement for improving self-organizing neural network topology preservation effect in prior art. The method comprises the steps of setting a network structure and a parameter of the self-organizing neural network, and normalizing input layer data; setting the number of input-layer neurons and the number of competition-layer neurons; performing rough adjustment on the weight vector of the competition-layer neurons of the self-organizing neural network, and obtaining a rough-adjusted competition-layer weight vector; by means of the rough-adjusted result, performing fine adjustment on the weight vector of the competition-layer neurons of the self-organizing neural network, and obtaining a fine-adjusted competition-layer weight vector; measuring the competition-layer weight vector, thereby obtaining a topology preservation reinforcing effect. The self-organizing neural network topology preservation reinforcing method has advantages of reducing difference between each competition-layer weight vector of the self-organizing neural network and an input sample, and improving topology preservation capability of the self-organizing neural network.
Self-organizing neural network topology preservation reinforcing method based on deep learning