Both new waveform convergence algorithm and latency algorithm are introduced to accelerate the rate of waveform convergence.
同时，给出了新的部分波形收敛算法和潜等算法，加速了波形的收敛速度。
The simulation results indicate that this algorithm not only guarantees global convergence, but also improves the converging rate and the stability effectively.
仿真结果表明，该算法不仅保证了全局收敛性，而且大大提高了算法的收敛速度和稳定性。
Then the mechanism of Simulated Annealing is import in the algorithm above to decrease the execution time and quickens the velocity of convergence.
然后，为了加快遗传算法的收敛速度减少算法执行时间引入模拟退火机制对上述算法进行优化。
The test functions show that the algorithm has better convergence speed and stability, the solving result is excellent.
通过测试函数表明该算法具有较好的收敛速度和稳定性，求解结果非常好。
For the basic differential evolution algorithm, the increasing quadratic function crossover operator was added to increase the convergence speed.
在基本差分进化算法中，融入递增二次函数交叉算子以增加算法的收敛速度。
Then some defects such as slow convergence rate and getting into local minimum in BP algorithm are pointed out, and the root of the defects is presented.
分析了BP算法的基本原理，指出了BP算法具有收敛速度慢、易陷入局部极小点等缺陷以及这些缺陷产生的根源。
All the possible algorithm models in general conditions have been considered, and parameter choice and convergence speed of these different algorithm were investigated.
考虑了在一般情况下各种可能的算法模型，分析了这些不同算法的参数选择问题、以及收敛速度问题。
Based on building up a model of echo canceller, the convergence of gradient-type stochastic adjustment algorithm of an adaptive filter under the mean-squared error criterion is discussed.
在建立回波抵消器模型的基础上，按最小均方误差准则，导出了自适应滤波器抽头的统计梯度算法和抽头调节的收敛公式。
This algorithm improves convergence speed and reduces residual error by increasing small the quantity of computation.
该算法通过增加很少的计算量不仅提高了收敛速度而且获得更小的剩余误差。
Then immune evolutionary algorithm is used to train the RBF network, which reduces the searching space of canonical evolutionary algorithm and improves the convergence speed.
采用免疫进化算法训练r BF网络，进一步缩小了标准进化算法搜索空间的范围，提高了算法的收敛速度。
Finally, a numerical example shows that the modified RLS algorithm result in faster convergence speed by solving the contradiction between speed and accuracy.
算例表明：改进的RLS算法能解决收敛速度与收敛精度之间的矛盾，有效地加快了收敛速度。
Computer simulation shows that the improved algorithm has better convergence performance than the conventional algorithm. It can speed up convergence rate and decrease state residual error.
经计算机仿真表明，新算法与原算法相比，收敛性能有所改善，收敛速度加快，稳态剩余误差减小。
A continuous simulated annealing algorithm with global convergence ability is applied to solve this controller parameters optimization design problem.
采用一类全局收敛的连续模拟退火算法完成了控制器参数的优化设计。
Particle Swarm Optimization (PSO) algorithm has existed premature convergence for multimodal search problems.
粒子群优化(PSO)算法对于多峰搜索问题一直存在早熟收敛问题。
By introducing the nonlinear variation weight and mutational operation into the standard particle swarm algorithm to ensuring the overall convergence and enhance the accuracy of convergence.
在标准粒子群算法中引入非线性变化权重和变异操作来保证全局收敛并提高收敛精度。
Detailed convergence results for the dual algorithm are given and it is proved that there exists a threshold, and the algorithm will converge if the penalty parameter is less than the threshold.
对这一算法给出了精细的收敛性结果，证明了存在罚参数的一个阈值，当罚参数小于这个阈值时，算法收敛。
The simulation and motor control show that the new algorithm has fast learning rate, good convergence properties and can overcome the defects of traditional PID algorithm.
仿真实验及在伺服电机转速控制中的应用表明，该算法具有较快的学习速度及良好的收敛性能，并有效地克服了传统PID算法的缺陷。
The algorithm is initialized by a statistical histogram based on FCM algorithm, which can speed up the convergence of the algorithm.
算法中使用基于统计直方图的快速FCM算法进行初始化，收敛速度大大提高。
Reliability, stability, convergence and fastness of this algorithm are satisfying.
这种算法的可靠性、稳定性、收敛性和快速性是令人满意的。
It is shown that this algorithm ensures convergence to a global minimum with probability 1in a compact region of a weight vector space.
关于算法分析的定理证明了这种混合算法对于紧致集内的权向量构成的任意连续函数能依概率1收敛于全局极小值。
Finally, the algorithm is tested by three test functions of numerical optimization. The emulational experiment results show that this improved algorithm has greater probability of convergence.
最后，用数值优化中的三个测试函数对该算法进行测试，仿真实验结果显示该算法可有效地提高算法的全局搜索能力。
Finally, the algorithm is tested by three test functions of numerical optimization. The emulational experiment results show that this improved algorithm has greater probability of convergence.
最后，用数值优化中的三个测试函数对该算法进行测试，仿真实验结果显示该算法可有效地提高算法的全局搜索能力。
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