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Given this matrix, we can show that and, where and.
Given this matrix, we can show that, where, and.
Through bus types and the node adjacency matrix, we can determine the type of each line.
Based on the state probability matrix, we can assess the system reliability by using EENS.
From this matrix, we can derive the matrix of technical coefficients water use.
By collecting vectors into a stoichiometry matrix, we can write (2) as (3).
By multiplying both sides of (11) with the unitary matrix, we can decouple the detection of two data blocks.
When the noise is nonwhite but has a known covariance matrix, we can still handle the problem through prewhitening.
By using the matrix, we can arrange the coefficient b n ( l ) of sine series in Theorem 2.3 as follows.
By using the matrix, we can display the coefficient a n ( l ) of cosine series in Theorem 2.1 as follows.
Thus, when dealing with optimization on the cost matrix, we can simply focus on η as a parameter.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com