Sentence examples for algorithm augmented from inspiring English sources

First, the nonlinear model of EHLS is developed, and then a Lyapunov-based control algorithm augmented with parameters update law is developed using back-stepping design method.

Distinct from the stabilizing feedback control design of the path-following problem for a single agent, the proposed feedback control algorithm, augmented with local disagreement terms, achieves consensus path-following.

The Max Min Ant System (MMAS) algorithm augmented with 3-opt local search is used as a framework for the implementation of the parallel ants and multiple ant colonies general parallelization approaches.

Li et al. [25] proposed a classification algorithm, augmented Lagrangian-multilevel logistic with a multilevel logistic (MLL) prior (LORSAL-MLL), which adopted an MLL prior to model the spatial information in the classification map from LORSAL algorithm.

Furthermore, a total of 16 different models, the baseline GARCH, their LSTAR-LST augmented two regime variants, the neural networks arhitecture and learning algorithm augmented models (i.e. RBF and MLP based 8 models) are ranked starting from the 1st towards the 4th model in terms of RMSE again.

However, we found that, on biological data, the third algorithm augmented with a few heuristics tends to identify DPs that are significantly smaller (and therefore more biologically plausible) than the former two algorithms (see Methods for details).

The simulation study shows that the 5CVN-adroit algorithm augments the routing issues such as delay, congestion, and deployment cost and it is justified based on the packet delivery ratio, average response time, routing overhead ratio, and packet collision ratio.

These systems will rely mainly on software algorithms, augmented by online collective human judgment.

The use of internal standards helps to correct migration time misalignments and it will also improve the efficiency of peak grouping algorithms augmenting the number of retrieved features.

In order to solve the proposed optimization problem, we develop an algorithm called augmented Lagrangian majorization minimization algorithm, which combines the split augmented Lagrangian shrinkage algorithm (SALSA) with majorization minimization (MM), and is guaranteed to converge for both convex and non-convex formulation.

The algorithm, MEPDEN, Memetic Elitist Pareto evolutionary approach based on the Non-dominated Sorting Differential Evolution (NSDE) multi-objective evolutionary algorithm which has been adapted to design RBFNs, where the NSDE algorithm is augmented with a local search that uses the Back-propagation algorithm.