Sentence examples for matrices defined for from inspiring English sources

To determine how the phylogenetic measures reviewed here were related to each other, to spatial distance, and to sample size, we conducted two convergence tests and a pairwise Mantel test for correspondence [27] for six distance matrices defined for the H5N1 hemagglutinin phylogeny.

To determine whether the phylogenetic measures reviewed here were related to each other or to spatial distance or sample size, we conducted global and a posteriori convergence tests and a generalized pairwise Mantel test for correspondence in CADM [27], [69] for six distance matrices defined for the H5N1 hemagglutinin phylogeny.

The WZ frame quantization level matrices define for which DCT bands parity bits are transmitted with each matrix entry indicating the number of quantization levels for the respective DCT band (0 means that no parity bits are transmitted for that DCT band).

with a constant matrix under transformation (1.6) if and only if there exists a regular real matrix defined for such that (2.7).

It is known that the maximum value of trace(Y T L Y) in (1) is equal to the sum of the M largest eigenvalues of L [27].1 Thus, in our clustering process, the number of clusters is determined based on the eigenvalues of the Laplacian matrix defined for the spectral clustering, i.e., as the number of eigenvalues that are larger than a threshold θ a.

where r m CFO ∈ ℂ KN × 1 is the received time domain vector, r m i ∈ ℂ KN × 1 is the time domain vector associated with user i, δ i is the CFO for user i relative to the carrier spacing (assuming N carriers), Φ i is a random phase for user i and z m is the noise vector d i ∈ ℂ KN × KN a diagonal matrix defined for user i by d i k, k = e j 2 π k δ i N (4).

Axelrod's A-matrix, defined for this purpose, rotates the incoming electric field polarization due to refraction at a lens while conserving the angle the field vector makes with the meridional plane [6].

In particular, probabilistic distributions of the two norms of correlation matrices defined in Part I are delivered for an arbitrary sample size and number of random variables in the case when the sampled values are ordered randomly.

In the same way, matrices are defined for other outputs.

Not all of the transfer matrices are defined for some countable set of energies.

As also mentioned in "Basic assumptions", when formulating our model, the investments amount depends on a parameter which is possible to be non-constant and to be fully controlled, i.e. to be equal to G = G ¯ k. (31)Hence under this assumption system (12) takes the form T k + 2 = M 1 T k + 1 + M 0 T k + G ¯ k (32 where M 0, M 1, the matrices as defined for the system (12).