Sentence examples for maximization parameters from inspiring English sources

A first alignment optimization was produced using the default simulated annealing algorithm while specifying parameters "-r 0.995 -k 10" to override Viterbi refinement and the resulting alignment was submitted to guided Baum-Welch expectation maximization (parameters "-B -i").

When v ( t ) varies with time, the maximization selects parameters giving relatively larger v ( t ) values where the observed votes are clustered in time.

In this paper, based on sparse Bayesian method, an expectation maximization-based parameter iterative approach is proposed to estimate the massive MIMO channel with unknown channel distribution.

Thanks to the availability of the source code and documented API it was possible to use BNs as a part of a larger probabilistic model using Expectation-Maximization for parameter optimization.

We found, however, that the only nest structure compatible with a priori assumptions under the utility maximization paradigm (scale parameters larger than unity) was one in which each vehicle make forms one nest.

Our aim was to characterize the influence of time-of-flight (TOF) and point spread function (PSF) recovery corrections, as well as ordered subset expectation maximization (OSEM) reconstruction parameters, in 82Rb PET/CT quantification of myocardial blood flow (MBF) and myocardial flow reserve (MFR).

In this paper, an expectation maximization (EM -based paramEM -basedative aparameters proposed to estiterative mapproachisO channel based on sproposedyesian metood.

In order to provide fairness while preserving the system throughput maximization, a new parameter is introduced which modulates this pure opportunistic resource allocation.

From a CR point of view, the maximization of the parameter in respect to the primary performance degradation tolerance, gives more opportunities for a secondary transmission (as the parameter is increased, the primary eigenmodes are released with a higher probability).

The optimal partition is performed using a classification-estimation (of densities -maximization-estimation (of parameters) algorithm.

High-quality RNA-seq reads obtained from filtering were aligned to the transcripts to estimate the transcript abundance using RSEM (v1.2.4) (RNA-Seq by Expectation Maximization) with the parameter of minimum and maximum fragment length of 200 and 300 respectively [ 56].