Sentence examples for the maximal likelihood from inspiring English sources

Out of these codewords, it then declares the one based on the maximal likelihood criterion.

Algorithm 1 shows how to train IDRN to get the maximal likelihood estimations (MLE) for the class prior (P(Y_i = c)) and conditional probability (P k|Y_i = c)), i.e., ({hat{theta }}_mathrm{c} = P(Y_i = c)) and ({hat{theta }}_{mathrm{kc}}=P k|Y_i = c)).

It is well known that source antenna switching (SAS) can gain additional diversity for the NDF protocol by using different antennas at the source in the first and second phases [15], and the maximal likelihood (ML) decoding is impractical because its computational complexity increases exponentially with the signal constellation size.

This is because threshold-free translation symmetry classifications can be based solely on the maximal likelihood position of a few Fourier coefficients (FCs) in the amplitude map of the discrete Fourier transform (dFT) of a more or less 2D-periodic image [17].

Hypothesized models were tested using the maximal likelihood procedure in the LISREL statistics program.

The optimal sub-population model was selected with the maximal likelihood K = 3 according to the ΔK method [ 39] and later corrections for ΔK artefacts [ 40].

Using simulated annealing [ 31] we have calculated the (maximal) likelihoods p that the connectivity correlation pattern shown in fig. 3a resulted from either an asymmetric process, or a symmetric process, respectively, by maximizing p with respect to f k and g k.

These MIMO-MAC codes are constructed from cyclic division algebras [23, 29] and have a linear-dispersion form [30]. Therefore, they can be decoded in the maximal-likelihood (ML) sense by a sphere decoder [31].

In the traditional MRC scheme, decisions-making is based on the maximal-likelihood (ML) rule (termed as MRC-ML) or the maximum-a-posterior-probability (MAP) rule (termed as MRC-MAP), both of which are equivalent for the equiprobable source [10] presents that the proposed DSC-D outperforms the traditional MRC-ML as well as MRC-MAP, and the performance gap becomes bigger with increasing SNR.

The log likelihood increases monotonically and reaches the approximate maximal likelihood after 50 twist iterations.

Duration histograms were constructed as described by Sigworth and Sine [33], and estimates of exponential areas and time constants were obtained using the method of maximal likelihood estimation.