convergence speed

Experiment shows that this algorithm has faster convergence speed and yields solutions close to optical value.

This algorithm has the advantages of fast convergence speed, small number of convergence and easy to get premature convergence.

But the convergence speed is still slow and the ICP algorithm may not converge to a global minimum.

adding in the mutation operator of pseudo-genetic algorithm speeds up the convergence speed in later optimization stage.

Acceding special operator into the presented model, both the calculation accuracy and the convergence speed can be improved.

However, the insistency between convergence speed and steady state error is difficult to be solved by the fixed step - size LMS.

The unstability integration number near the Gauss point is overcome, and the calculating precision and the convergence speed are improved.

Results of the experiments indicate that the mutation operation has high searching efficiency and fast convergence speed.

The diagnosis accuracy and convergence speed of the algorithm are further improved by orthogonal experiment and limiting search space.

The simulation results indicate that the convergence speed and accuracy of global optimization is significantly improved.

Simulations show that the new algorithm is superior to the traditional linear constraints algorithm in BER and convergence speed.

The example result shows that in the genetic algorithm the optimum global solution can be gained and the convergence speed is fast.

Test results show that the new algorithm has faster convergence speed and better global optimization ability in the multi-dimensional space.

The hybrid genetic algorithm features less infeasible solution, higher convergence speed and can avoid premature convergence.

This can greatly strengthen the cooperation between ants, accelerate the convergence speed and enhance the global searching ability.

Experiments show this algorithm has a faster convergence speed and the dither signal can be removed effectively.

For achieving faster convergence speed and higher tracking capability, variable step-size and momentum factor must be used.

Testing results show that the proposed algorithm has both good whole astringency and fast convergence speed.

Simulation results show that the filtering algorithms have faster convergence speed.

With an adventure acceptable probability and fast annealing, VFSA can improve the convergence speed.

By theoretical and numerical analysis, the two proposed methods have better convergence speed than the classic golden section method.

Meanwhile the strategy of elitist individual migration and turbulence enhance the convergence speed.

In the meantime, the mutation operator is brought in the gradient direction to accelerate the algorithm convergence speed.

The experiment shows that the algorithm avoids the local optima and increases the convergence speed.

To improve the convergence speed of sliding mode variable structure control, a new nonlinear sliding mode surface is proposed.

Based on this division, with the method of iteration, the influencing factors and formulas for convergence speed are deduced and discussed.

The experiments indicate that the convergence speed and precision of BP networks using the improved algorithm are enhanced greatly.

Test result indicates that the improved PSO advanced distinctly in performance like convergence speed and convergence rate. 2.

Simulation shows that the learning algorithm has a fast convergence speed and good stability.

The main features of DE are simple to use, fast convergence speed and few field knowledge needed.

The calculation cases show that convergence speed of medium and small scale train operation diagram is faster.

The result shows: the fusion arithmetic after training has high plot precision, quick learning and convergence speed.

Simulation results show that the analog-digital mixed ADC design have the advantages in the performace of BER and convergence speed.

Convergence speed is improved by optimal initialized parameter.

New algorithm corrects values of coefficient row-by-row and has an increased convergence speed.

The simulation results show the more rapid convergence speed and better echo canceling under the single-talk condition.

The experiment using Rosenbrock function shows that both the precision and the convergence speed are better.

Based the improvement, the algorithm has the fast convergence speed and the high accuracy.

However, BP network with gradient descent has some defects such as low convergence speed, fall in local minima.

Simulation results show that APSO not only effectively alleviates the problem of premature convergence, but also has fast convergence speed.

Simulations results show that the error convergence speed and accuracy of NN when trained by PF is better then by BP and EKF;

Effect of calculation parameters on convergence speed of one-dimensional transient heat transfer series solution

The Nonlinear Binding Optimization Programme of Convergence Speed

Convergence Speed of Evolutionary Algorithm

Analysis of convergence speed of repetitive control system

The Convergence Speed of Ant Colony Optimization

Optimum algorithm of S-boxes based on fast convergence speed genetic algorithm