Complex-valued neural networks for the Takagi vector of complex symmetric matrices
作者： Xuezhong Wang , Maolin Che , Yimin Wei
DOI: 10.1016/J.NEUCOM.2016.10.034
关键词: Mathematics 、 Symmetric matrix 、 Artificial neural network 、 Toeplitz matrix 、 Complex differential equation 、 Convergence (routing) 、 Representation (mathematics) 、 Applied mathematics 、 Discrete mathematics 、 Singular value 、 Factorization
摘要: Abstract This paper proposes complex-valued neural network for computing the Takagi vectors corresponding to largest value of complex symmetric matrices. We establish some properties network. Based on factorization matrices, we an explicit representation solution and analyze its convergence property. Under certain conditions, design a strategy matrix by proposed As application, consider left right singular associated with Toeplitz illustrate our theory via numerical examples.
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