A NEW METHOD FOR EIGENSTRUCTURE EXTRACTION AND ITS NEURAL NETWORK IMPLEMENTATION
一种新的特征结构提取方法及其神经网络实现

The cost function for eigenstuctures extration is discussed in detail, one can obtain the largest eigenvector by minimizing the cost function. In order to obtain the other eigenvectors, a covariance matrix series is constructed. If one compares the cost function with the energy function of a neural network, the neural network can be introduced to extract the eigenvectors. Theoretical analysis and simulations show that the proposed method is reasonable and feasible.