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Method for determining true spectrum from measurement spectrum

机译:从测量光谱确定真实光谱的方法

摘要

(57) in determining the true spectrum from the measured spectrum using [Abstract] maximum entropy algorithm, to determine the eigenvalues ​​of (10 5 to 10 4 is the order of N) N × N-type matrix of large dimension impractical most, or, it is not practical at all in some cases. In accordance with the present invention, a large matrix of this type is divided into sub-matrices large number of very small it is the main diagonal of the diagonal or larger matrix. The set of eigenvalues ​​to be determined is formed by eigenvalues ​​of the submatrices of all can be determined more quickly. Because of the characteristics of the Toeplitz matrix part, these eigenvalues ​​can be determined very quickly by using the Fourier transform of a single row of the submatrix. Thus by using the set of eigenvalues ​​obtained, the true spectrum is determined by using a minimization algorithm. Convergence speed of the minimization algorithm is significantly improved by adding the variable minimization process of random noise, to reduce to zero the iteration step a number of the random noise values.
机译:(57)在使用[摘要]最大熵算法从实测光谱中确定真实光谱时,确定特征值(10 5 到10 4 的阶数N)N×N型大尺寸矩阵最不切实际,或者在某些情况下根本不实用。根据本发明,这种类型的大矩阵被分成大量的子矩阵,非常小的子矩阵是对角线的主对角线或较大的矩阵。由所有子矩阵的特征值组成的待确定特征值集合可以更快地确定。由于Toeplitz矩阵部分的特性,可以通过使用子矩阵的单行的傅立叶变换非常快速地确定这些特征值。因此,通过使用获得的一组特征值,可以使用最小化算法确定真实频谱。通过添加随机噪声的变量最小化过程,将许多随机噪声值的迭代步数减少到零,极大地提高了最小化算法的收敛速度。

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