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The design method involves linear matrix inequality (LMI) optimization techniques and the generalized structured singular value üg.
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The method involves two linear programming (LP) models to find the steady optimal fluxes of reactions and the mass flows of metabolites in both pathologic state and medication state, meanwhile taking the side effects of drug action into account.
This often involves linear system solvers based on iterative and multigrid methods which may limit the ability to scale to large numbers of processors.
Fusion methods that involve linear forward and backward transforms had been classified by Sheftigara [48] as component substitution methods.
The second variant involves linear optimal estimates.
The first step involves linear phase processing.
The method involves solving a linear system of equations, which can be readily implemented in a distributed fashion.
In brief, this method involves fitting a linear model for each gene in the data and moderating the standard error via an empirical Bayes method.
This method involves the non-linear least squares method without an independent variable.
The method involves a trajectory based linearization and employs a model bank with a set of local linear models for each discrete operational mode.
The PSTS method involves pitch-synchronous-time scaling of the linear prediction (LP) residual waveform of the speech signal.
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