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This is an extension of the maximum likelihood criterion.
A maximum likelihood criterion is developed to detect overlapping points in MRIs.
paper, which combines a maximum likelihood criterion with a sensitivity measure.
Out of these codewords, it then declares the one based on the maximal likelihood criterion.
The different parameters are estimated by using the Maximum Expectation of joint Likelihood criterion.
The maximum likelihood criterion is entirely based on the MLE method.
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A preliminary CFO/channel estimate is first reached based on the maximum-likelihood criterion.
Informally, a penalized log-likelihood criterion is used to select a piecewise polynomial.
Decision trees are constructed iteratively through a greedy and top-down procedure which maximizes the log-likelihood criterion [34, 35].
Mixture parameters (weights, means vectors, and covariance matrices) are estimated by the Expectation Maximization algorithm (EM) which maximizes the log-likelihood criterion.
The number of clusters was automatically determined on the basis of Schwarz Bayesian Criterion, and as the type of distance measure, the log-likelihood criterion was used.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com