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where 1 is an appropriately dimensioned unit vector.
Using the Newton-Leibniz formula, for any appropriately dimensioned matrices N i, M i, the following equations are true: (14).
end{aligned} (mathcal{P}) is the appropriately dimensioned square permutation matrix such that mathcal{P} [a_{1} quad a_{2} quad cdots quad a_{2m} ] = [ a_{1} quad a_{3} quad cdots quad a_{2m-1} qua_{2_{2} quad a_{4} quad cdots quad a_{2m} ].
Denote 〈 x, H y 〉 T = ∫ 0 T x T ( t ) H y ( t ) d t, in this article, we focus our attention on the quadratic supply rate E ( v, e, T ) = 〈 e, Q e 〉 T + 2 〈 e, S v 〉 T + 〈 v, R v 〉 T, where Q, S, R are appropriately dimensioned, and Q, R are symmetric matrices.
if there exist symmetric matrix P = P T > 0, any appropriately dimensioned matix V and a given scalar ?, such that the following inequality hold: [ - V A T - A V T - B P + V T - ? V A T V C T * - ? 2 I - ? B T D T * * ? V + ? V T 0 * * * - I ] < 0. (7).
where the scalar ?, symmetric matrices P ˆ 11, P ˆ 22, and appropriately dimensioned matrices P ˆ 12, X, Y, U, A ˆ, B ˆ, C ˆ, D ˆ could minimize ? in the LMI (16) subject to LMIs (15) and (16), and N, M are deduced from U - Y X. Proof It is obviously that the equations (28), (29), (30), (31) are deduced from (18), (19), (20), (21).
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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