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And so, what I'm trying to say is that when you have a general change of variables, du dv versus dx dy is given by the determinant of this matrix of partial derivatives.
It is based on the mathematical model of the difference between the control and target parameters, henceforth the matrix of partial derivatives of the system is solved.
Substituting back into \ \bF\) and expanding to first order in \(\varepsilon(t)\) (considering only the perturbations at \(t = 0\) and dropping the explicit dependence on \(t\) from \(\varepsilon)\) yields where the matrix \ \bJ \bx)\) is the \(n\times n\) Jacobian matrix of partial derivatives of \ \bF\) evaluated at the point \ \bx\).
Besides, there are also some minimal regularity prerequisites, called conditions C1 C2, the most stringent of which being that the matrix of partial derivatives of ( {text{p}}^{text{i}} left( {mathbf{x}} right.,{mathbf{u}},left. {text{t}} right) ), with respect to the m variables u, has rank l.
The generalized Jacobian of a function (g: mathbb{R}^{p} tomathbb {R}^{q}) at x̄, denoted (partial_{c} g(bar{x})), is the convex hull of all matrices M of the form M=underset{n to+infty}{lim} Jg(x_{n}), where (x_{n}tobar{x}), g is differentiable at (x_{n}) for all n, and Jg denotes the (qtimes p) usual Jacobian matrix of partial derivatives.
end{aligned} (15) V, the matrix of partial derivatives can then be written in a compact matrix form as: V^{mathsf{T}}=2 begin{bmatrix} langle{ psi _{mathrm {g}}}vert P_{1} vdots langle{ psi _{mathrm {g}}}vert P_{M} end{bmatrix} bigl(E_{0} I_{n}-H({{lambda }} bigr)^ bigl[H_{1} vert {psi _{mathrm {g}}} rangle quad cdots quad H_{K} vert {psi _{mathrm {g}}} rangle bigr].
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In contrast, for full-matrix least squares we need the matrices of partial derivatives and.
The aim of this paper is to give not only the matrix representation of partial Hecke-type operators by means of Bernoulli polynomials and Euler polynomials, but also functional equations and differential equations related to partial Hecke-type operators and special polynomials.
H x) is the Hessian matrix of second partial derivatives of ψ evaluated at the fixed point (assumed to be x = 0).
Important metrics of the bond strength and character are the electron density at the BCP, ρ(r BCP), and the Laplacian of the electron density at the BCP, ∇ρ(r BCP), which itself represents the 3 × 3 Hessian matrix of second partial derivatives of the electron density with respect to the coordinates.
Useful metrics of the bond strength and character are the electron density at the BCP, ρ(r BCP), and the Laplacian of the electron density at the BCP, ∇ρ(r BCP), which represents the 3 × 3 Hessian matrix of second partial derivatives of the electron density with respect to the coordinates.
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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