Sentence examples for matrices that reflect from inspiring English sources

Even externalists, however, can define 2D matrices that reflect the subject's epistemic perspective on the reference of her words and thoughts.

Whole blood and plasma are emerging exposure matrices that reflect a shorter half-life (i.e., about 1 hr) compared to arsenic levels in urine (4 days) (NRC 1999).

In our processing, a feature matrix that reflects the texture prior of object contour is firstly constructed.

where f is the frequency in Hz, l is the loop-length in meters, H diag ( d ) = diag H ( d ) is a diagonal matrix of the DM channel H d), I is the N × N identity matrix, and C d)is a zero-diagonal matrix that reflects the crosstalk coupling dispersion (and extend the 99% crosstalk model) as per the existing standard, including the phase.

Let the constant population projection (Leslie) matrix that takes the population from any time t − 1 to time t be denoted by A. Here, with a life expectancy at birth [e(0)] of 85 years, A is a 17 × 17 matrix that reflects the age groups (0,5) through (80,5).

A variety of methods for isolating the motifs have been developed, but all are based on identifying short highly conserved patterns within the larger alignment and constructing a matrix similar to a substitution matrix that reflects the amino acid or nucleotide composition of each position in the putative motif.

The characters were coded as presence/absence in a binary matrix that reflects the presence of characters used by a particular tribe in any of their textiles.

Our statistical models incorporated phylogeny by representing the error term of the statistical model as a variance-covariance matrix that reflects the phylogenetic relationships among the species [88].

As part of the genome alignment process, progressiveMauve (Darling et al. 2010) generates a pairwise genome content distance matrix that reflects the proportions of the genomes that are included in the initial set of local alignments.

In a next step, ALE values at all voxels in the rest of the brain were combined into a functional co-activation matrix that reflected how likely each seed voxel co-activated with any other voxel in the brain (cf. Eickhoff, Bzdok et al. 2011).

The procedure is based on representing the network as a matrix of probabilities that reflect random walks on a simple graph, similar to that used in the well-known Markov Clustering (MCL) algorithm [ 9].