Sentence examples for mutual information content from inspiring English sources

Registration was accomplished with an automated algorithm that maximized the mutual information content of the image volumes.

While the Pearson correlation coefficient indicates the existence of correlations and anti-correlations between different parts of the spectra, an analysis of the mutual information content between the different spectral components reveals direct experimental evidence for the existence of a mutual dependence between them.

Functionally linked genes in this study are defined as the genes that satisfy thecutoff criteria of 0.9 for mutual information content and 0.8 for Pearson correlation coefficient as these values differentiated the real from random data.

The E-values obtained via SSEARCH were normalized [8] such that it enables capture of sequence divergence as well as generates continuous variables which are amenable to rigorous statistical treatment such as estimating mutual information content using B-spline function.

Functionally linked genes were inferred based on calculation of mutual information content using mis_calc program [31], Pearson correlation coefficient and Hamming distance (using an in-house developed perl script).

For example, Spearman's correlation coefficient (SCC), mutual information content and partial correlation have also been used in gene coexpression studies.

It defines the concepts of variable, alphabet, spaces of definition, uncertainty, entropy, mutual information, information content, acceptance margins, tolerances, response margins, and transfer function.

Additionally, by comparing experimental conditions with the same number of feedback events (sounds), but varying in the amount of information feedback conveys about outcome (the mutual information), we can test if information content has an effect on performance.

The maximum mutual information is the system capacity.

Entropy, conditional entropy, and mutual information are fundamental metrics that comprise information theory, and can, by definition, describe the information contents of a single variable as well as of the association between two variables.

The information content of for the j-th observation x j is the mutual information between z j and x j as where H is the entropy.