Abstract
The cost function for eigenstructures extraction is discussed in detail in this paper, one can obtain the largest eigenvector by minimizing the cost function. In order to obtain other eigenvectors, a covariance matrix series is constructed. If one compares the cost function with the energy function of a neural networks, the neural networks can be easily introduced to extract the eigenvectors. Theoretical analysis and computer simulations show that the proposed method is reasonable and feasible.
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Shuijun, Y., Diannong, L. A new method for eigenstructures extraction and its neural networks implementation. J. of Electron.(China) 13, 211–215 (1996). https://doi.org/10.1007/BF02685829
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DOI: https://doi.org/10.1007/BF02685829