Maximum Likelihood (ML) method has an excellent performance for Direction-Of-Arrival (DOA) estimation, but a multidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use.
Because MLSE is an NP-complete problem, there are a number of possible "good" solutions in the multidimensional solution space.
However, it can still be considered a valid and accurate method for the screen of the multidimensional solution space, when the objective is the determination of separating hyperplanes that maximize discrimination between different classes.
The simulated statistical bubble quantities are computed from voidage signals derived from the transient multidimensional solution of two-fluid models.
Over the last decades, heuristic optimization methods based on imitating natural, biological, social or cultural processes on a computational level have aroused the interest of the scientific community due to their ability to effectively explore multimodal and multidimensional solution spaces.
Recently several consensus-based motif finding algorithms have been developed using evolutionary algorithms, because of their efficiency in searching over multidimensional solution spaces.
The 3D solution structure of N- HvGR-RBP1 was solved using well-established, heteronuclear (H, N, C), multidimensional solution NMR experiments and standard computational torsion angle simulated annealing protocols.
This analysis suggests that workload created by alerts is a complex barrier needing multidimensional solutions.
