regina_lee
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Let e_i be a unit vector with one 1 in the i-th element. Is the following expression has a recursive presentation?
$$y_N = \sum_{k=0}^N {\frac{{{X^k} e_i}}{\|{{{X^k} e_i}\|}_2}} $$
where X is a n \times n square matrix, and {\| \cdot \|}_2 is a vector norm defined as {\|z\|}_2 = \sqrt{|z_1|^2+|z_2|^2+...+|z_n|^2}.
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EDIT: I know that if y_N = \sum_{k=0}^N {{X^k} e_i}, it is easy to obtain the following recursive formula:
$$y_{k+1} = X y_{k} + e_i, \quad (k=0,1,2,...) \textrm{ with } \ \ \ y_0=e_i$$
However, after we add a normalized factor, is there a similar recursive expression? Thanks.
$$y_N = \sum_{k=0}^N {\frac{{{X^k} e_i}}{\|{{{X^k} e_i}\|}_2}} $$
where X is a n \times n square matrix, and {\| \cdot \|}_2 is a vector norm defined as {\|z\|}_2 = \sqrt{|z_1|^2+|z_2|^2+...+|z_n|^2}.
---
EDIT: I know that if y_N = \sum_{k=0}^N {{X^k} e_i}, it is easy to obtain the following recursive formula:
$$y_{k+1} = X y_{k} + e_i, \quad (k=0,1,2,...) \textrm{ with } \ \ \ y_0=e_i$$
However, after we add a normalized factor, is there a similar recursive expression? Thanks.