convergence rate

The result of the simulation show GA is effectively speed up the convergence rate, especially in large-scale DS-CDMA cellular system.

The slow convergence rate and premature convergence of the pure genetic algorithm are avoided by means of increasing the race individuals.

And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.

In the numerical simulation, the proposed algorithm is compared with the basic MCMA in terms of convergence rate and stationary error.

The convergence rate can be the limit of adaptive optics without a wave-front sensor in real time applications.

The particle swarm optimization algorithm which has slow convergence rate and was easily trapping in local optimum was improved.

Linear search is incorporated into the inversion method to improve the speed of the convergence rate of inversion.

The results show that the effective mechanism can improve the convergence rate of clustering and classification results.

The algorithm resetting of the convergence of the conjugate gradient is also employed to speed up the convergence rate.

The improved algorithm is experimentally to have better restoration effect and faster convergence rate.

In addition, when a certain error bound holds locally, the author analyzes the convergence rate of the iteration sequence.

We obtain an upper bounded estimate for the convergence rate of the piecewise linear interpolation.

Global convergence and local superlinear convergence rate of the proposed algorithm are established on some reasonable conditions.

Numerical results validate the second-order convergence rate of our scheme on many highly distorted meshes.

Using "temperature-raising" strategy, convergence rate and training speed of the algorithm are greatly improved.

The simulation results show that the method may enhance the convergence rate and reduce the circular arrays sidelobe levels effectively.

dynamic cross-rate and cross-rate variability and variation, speed up the convergence rate.

Simulation results show low complexity, fast convergence rate, and low misadjustment of the proposed algorithm.

Every iteration method has it applied condition. We need to check the iteration method's convergence property and its convergence rate.

The numerical simulation show the control system has asymptotic stability, faster convergence rate and higher control accuracy.

Comparing with Evolutionary Particle Swam Optimization, the classifier fastens the convergence rate.

The convergence rate is analyzed theoretically and simulated with quadrature amplitude modulation(QAM) signals.

Through the dynamic system FCRNN design , convergence rate and error precision of the improved algorithm get perfect effect.

During the search process of PSO, the chaotic local optimizer was introduced to raise its resulting precision and convergence rate.

We also proved that our convergence rate is better than existing results.

Moreover, convergence rate of absorbing parties is positively related to R&D investment and diffusion speed of diffusing parties.

The simulation results show the proposed method has a faster convergence rate, and can efficiently meet the need of true height estimation.

Simulation results show that the method has a faster convergence rate and better estimation performance.

The global convergence and local quadratic convergence rate are proved under standard assumptions.

Then the optimal convergence rate of the cascadic multigrid for the velocity is proven.

N step restart conjugate gradient routine is used to speed up the convergence rate.

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

The restraining result showed that the improvement model has the distinct enhancement in the convergence rate.

The length formula of sine function is a stagger progression, its calculation is hard and convergence rate is slow.

A novel blind equalization algorithm with rapid convergence rate is proposed to receive the burst-mode signal.

Compared with BP neural network, B-spline fuzzy neural network has the advantages of fast convergence rate and local learning ability.

Furthermore, ImSTINT has faster convergence rate and better suppression performance against main lobe clutter.

Then, convergence and convergence rate become a very important problem we must consider.

Thus genetic algorithm could avoid redundant search and the convergence rate will be improved greatly.

Second, Reference function value is likely much larger than the function value, which is bad for convergence rate.

This algorithm has higher convergence rate in the experimental test so that case indexing is more efficient.

At the same time, in order to quickening the convergence rate, give other two dynamical iterative formats.

A Projection-type Method of the General Variational Inequalities and Its Convergence Rate

Convergence rate of empirical Bayes estimation of measure functions for parameter in two-side truncated distribution families

Strong Uniform Convergence Rate of Nonparametric Kernel Estimate of a General Function under Dependent Data

Finite Element Estimate for Nonparametric Autoregressive Functions and its Convergence Rate

A Study about Convergence rate of a Monte-Carlo Method for American Option Pricing

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Exponential Convergence Rate Estimation of a Class of Large-Scale Systems with Variable Delays

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Strong Convergence Rate of Nonparametric Regression Estimates with Censored Data

Strong Convergence Rate of Recursive Probability Density Estimator for NA Sequences

Estimate of Exponential Convergence Rate and Exponential Stability for High Order Hopfield Type Neural Networks

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Strong law of large numbers and convergence rate of pairwise NQD random sequences

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Strong Convergence Rate of Sums for NA Sequences with Different Distributions

Comparison of Convergence Rate and Analysis of Robustness by Using Different Algebraic Equation Solution Methods

Another Algorithm for Improving the Convergence Rate of BP Neural Networks

Submartingale Analysis of Convergence Rate Genetic Algorithm

On the Approximation Problem for Fixed Points of Strictly Pseudocontractive Mappings and Convergence Rate Estimate

Laws of large numbers and convergence rate formultidimensionally indexed random variable sequences

The Convergence Rate and Efficiency of Evolutionary Algorithms

The Estimate of Convergence Rate for the Oblique Projection Method

Analysis of the convergence rate on Newton iteration method

On the Convergence Rate of Complete Convergence

Analysis of Convergence Rate for Iterative Learning Control

Selection of relaxation factor and convergence rate for D-N DDM over unbounded domain,

Linear Convergence Rate of Supermemory Gradient Method

Convergence Rate of Row Action Method for System of Linear Equations

controlling the convergence rate in the process of image enhancement;

Laws of large numbers and convergence rate for NA sequences