Sentence examples for mutual information means from inspiring English sources

The concept of TE extends from the concept of mutual information, which is a measure of mutual dependence between two time series and more mutual information means less uncertainty if knowing one time series.

Zero mutual information means that the joint distribution of the personal genome-disease association contains no more information than the personal genome-disease relationship considered separately.

The information entropy of DWI-MRI and CT fusion is larger than that of T1-MRI; however, parameters of the mutual information, mean grads, and spatial frequency are all smaller than those of T1-MRI fusion results (Table 3).

In order to comprehensively evaluate the fusion algorithm of this paper, the thesis selects the information entropy, mutual information, mean grads, and spatial frequency to reflect the image fusion evaluation parameters [22 25].

The Csiszar's f-divergence Γ f incorporated most of special cases of probability measure distances, including the variation distance, χ 2 -divergence, information for discrimination or generalized entropy, information gain, mutual information, mean square contingency, etc. Γ f has many applications to almost all applied sciences where stochastics enters.

Furthermore, the utility function can be defined with the mutual information, which means the information of conveyed by the new measurements [18].

The features used are a standard 6-feature set, including the Z-score of the MFE, structure conservation index, mean entropy of stems, mean mutual information of stems, mean pairwise identity and number of sequences [ 17, 19], and neutrality, which is calculated using the measures described above.

Meanwhile, the numerous image data will be objectively assessed and compared from several aspects such as information entropy, mutual information, the mean grads, and spatial frequency.

The main optimizing processing of an AF MIMO relay system is to maximize or minimize objective functions, such as mutual information (MI), mean square error (MSE), sum of rate and signal-to-interference-plus-noise ratio (SINR).

Overall, we believe that both the mutual information and the mean squared error have their own domains of superiority, and we think that the mean squared error is a more appropriate fit for this paper.

In [27], the author investigated the linear precoding and power allocation policies to realize the optimal resource allocation for general multiple-input-multiple-output (MIMO) Gaussian channels with arbitrary input distributions, by capitalizing on the relationship between mutual information and minimum mean-square error (MMSE).