For μ a given measure and φ a regular optimality criterion, function of the information matrix, we consider φ-optimum design measures ξα∗ that maximise φ under the constraint ξα∗⩽μ/α, α given in (0,1).
For the matrix, we consider water, ice, and polymer.
Then, by taking each row of the MPR matrix, we consider all the possible cases where from 1 to (tilde {R}) packets are transmitted.
Instead, since we can estimate the noise-only covariance matrix, we consider obtaining a better approximation to the true noise-plus-reverberation eigenvalues by correcting the eigenvalues of the noise-only covariance matrix with a correction factor.
To evaluate the effects of the quantization step size matrix, we consider a weighted sum of all the elements m Q where the averaging factor, a, for each element depends on the corresponding frequency.
In this work, we consider a simple extension of SSA where instead of analyzing a single trajectory matrix, we consider a compound trajectory matrix generated by the concatenation of S individual matrices, i.e., (mathbf {M}=;[mathbf {M}_{1}, mathbf {M}_{2}, ldots, mathbf {M}_{S}] in mathbb {R}^{S(K times L }).
We encode this migration rate using the matrix We consider two individuals, i and j, each sampled from either population.
For creating document-word matrix, we consider each GO concept as a document and use the name field ('GO term') in GO for extracting terms of the node.
Figure 7 implies that all the sampling matrices we considered except the Fourier matrix have satisfactory coherence requirements.
To avoid pairs of similar matrices, we considered only combinations of PWMs, which overlapped in less than 10% of the hits of the PWM with the lower total number of matches at a score P-value threshold of 0.001.
