Your English writing platform
Discover LudwigSuggestions(5)
Exact(18)
X stands for the SA-ISAR echo matrix, as defined before.
The matrix, R s s, assumes the form of a TBT matrix as defined in ([6], Equation (20)) for the 2-D spatially correlated network.
That is T T ⊲ =I J, where ⊲ denotes the transpose-conjugate of a quaternion matrix as defined in [11] and I J the J×J identity matrix.
We now show that the upper bound given in (30) is attainable when is Gaussian with covariance matrix, as defined in (23).
The matrix, R ds ′, has the form of a non-symmetric TBT matrix as defined in ([6], Equation (27)) for the 2-D spatially correlated network.
In order to verify that the above algorithm is correct, it suffices to substitute in (49) with the element of the matrix as defined in (21).
Similar(42)
Given such a sampled network, a data matrix X (as defined in Section 2.2) was constructed.
It can be shown that the aggregate uplink achievable throughput can be formulated using (2), as in (3), where and are binary elements of coverage matrices, as defined in Table 1.
The goal is to learn the appropriate weights w for combining the cost matrices as defined in Equation (4) such that for each worm the solution is close to the true labeling, y.
In this case, the problem of how to construct the Cauchy matrix is solved analytically thanks to a delayed matrix exponential, as defined below.
While the sensitivity matrix S as defined in equation (7) describes all responses in one matrix, is created for each response r i separately.
Write better and faster with AI suggestions while staying true to your unique style.
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