Your English writing platform
Discover LudwigExact(4)
In [9], a decentralized consensus optimization algorithm was derived to estimate the spectrum, where an l 1-regularized least square problem was solved at each CR user.
First, a classification algorithm was derived to distinguish diverse cancer phenotypes from normal phenotype tissues.
An algorithm was derived to divide these admissions into categories based on their reason for admission.
The first two log likelihoods on the righthand side of equation (7) are then expressed as A closed system of the EM algorithm was derived to estimate these haplotype frequencies (see the Text S1).
Similar(54)
From there a convergent belief optimization algorithm is derived to minimize the Bethe free energy.
A fast and simple-to-implement computational algorithm is derived to perform the variable selection and forecasting tasks simultaneously.
Moreover, a proportional integral learning algorithm is derived to speed up the convergence of the tracking error.
A Monte Carlo algorithm is derived to solve the one-dimensional telegraph equations in a bounded domain subject to resistive and non-resistive boundary conditions.
After the construction of robust probabilistic model, the iterative expectation maximization algorithm is derived to perform the parameter estimation for both single and mixture models.
After formulating this design as an unconstrained minimization problem, two algorithms based on the majorization minimization method and a gradient-based algorithm are derived to deal with this problem.
Moreover, modified versions of the proposed algorithm are derived to tackle the complementary set design problems in which low peak-to-average-power ratio (PAR), unimodular or phase-quantized sequences are of interest.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com