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。
All the possible algorithm models in general conditions have been considered, and parameter choice and convergence speed of these different algorithm were investigated.
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。
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.
并在仿真测试中对该模型的性能进行了分析，证明该模型在收敛时间，节点查询速度，和对扰动的适应性方面优于传统的模型。
The simulation results of the model performance are analyzed to prove the convergence time, node querying speed and adaptability to churn are better than the traditional model.
通过与BP算法的仿真结果比较分析，发现该算法具有稳定性好，收敛速度快，预测精度高的特点。
According to the analysis of simulation results compared with BP algorithm, this algorithm has the advantage of the fine stability, fast convergence speed and high precision.
支持向量机(SVM)是一种新的通用学习机器，它从结构风险最小化的角度，分析了学习过程的一致性、收敛速度等。
Support vector machine (SVM) is a new general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.
理论分析和大量实验结果表明，本文算法具有收敛速度快和稳定性好。
Theoretical analysis and experimental data show that the new (IES) has high converge speed and stability.
理论分析和计算机仿真实验均表明，新算法与传统的恒模算法相比，具有更快的收敛速度和更小的稳态剩余误差。
The theoretical analysis and the simulation results proved to show that the new algorithm has improved performance of the convergence speed and residual error than traditional CM algorithm.
计算机仿真结果与理论分析相一致，证实了该算法比通常的补对算法和传统的LMS算法有更快的收敛速度。
Computer simulation results confirms the theoretical analysis and shows the new algorithm provides faster convergence speed than the complementary pair algorithm and usual LMS algorithm.
经计算机仿真与理论分析表明，该算法与传统恒模算法相比，收敛速度加快，稳态剩余误差减小。
Computer simulations and theory analyses show that the proposed algorithm can speed up convergence rate and decrease state residual error compared with conventional CMA blind equalization algorithm.
借助于全局误差界的分析，证明了所提方法具有R -线性收敛速度。
By means of analysing the global error bound, we prove that the method has a R-linear convergence rate.
利用改进的BP网络和RBF网络进行了短期电力负荷预测，并对训练的收敛速度和预测精度进行了分析。
By the improved BP and RBF neural networks, short-term electric load is forecast and training (convergence) rate and forecasting precision are analyzed.
通过与BP算法的仿真结果比较分析，发现该算法稳定性好，收敛速度快，预测精度高。
Through the analysis of simulation results as compared with BP algorithm, this algorithm has the advantages of fine stability, fast convergence speed and high precision.
分析和仿真结果表明，该类自适应多用户检测器具有更好的收敛速度和较为简单的结构，具有广泛的应用前景。
Analysis and simulation results show that this kind of detector has faster constringency speed and its structure is simple, so it has good potential for practical applications.
理论分析和计算机仿真实验均表明该算法与传统的恒模算法相比，都具有更快的收敛速度和更小的稳态剩余误差。
Theoritical analyse and computer simulation both shows the new one has faster convergent speed and less steady error than traditional constant-modulus algorithms.
算法分析表明，并行遗传算法可以有效地提高收敛速度。
The results indicate that parallel genetic algorithms can improve convergence speed efficiently.
分析表明，这种变步长搜索的模糊控制器收敛特性好，速度快。
The analysis has showed that this kind of fuzzy controller with variable searching steps has better convergence character and its adjusting speed is quick.
比照传统遗传算法与生物界进化过程，分析了引起传统遗传算法收敛速度慢和寻优效率低的两个原因。
By contrasting the traditional genetic algorithms (TGA) with the biologic evolution, two kinds of reasons that the convergence speed and searching efficiency in TGA are both lower are concluded.
LDPC码译码误比特率与迭代次数关系曲线及其粘滞点的研究，对于进一步深入分析译码机理和加快译码收敛的速度有着重要的意义。
Research of the fixed point which appears in decoding process of LDPC codes is important to further analyze the decoding mechanism and speed up decoding convergence.
分析表明，两者结合比改进前具有更快的收敛速度，能得到更多的最优解。
Analysis show that the convergence rate is improved and more optimal solves are found with both 'switch operator' and 'ants out' strategy.
并对以前神经网络中的两个难点：局部极小和收敛速度慢的问题进行分析。
Our previous work has shown that the network was effective in improving two difficulties, a convergence to local minimal and a slow learning speed.
分析了本方法的主要误差来源，并由此提出了四个重要的技术措施来保证本方法的计算精度和收敛速度。
Analysed main error source of this method, putting forward four important technology to guarantee the precision of calculation and convergent velocity of this method.
分析结果证明，PSOGA算法的收敛速度优于GA算法。
Experimental results prove the convergence rate of PSOGA is much faster than GA's.
分析了此守恒重映方法的收敛性与守恒性，研究了积分控制体对速度计算的影响。
Further, the convergence and conservation of this remapping method are analyzed, and the influence of the integral control system to calculate velocity is studied.
并将其应用到基于溶解气体分析的变压器故障诊断中，实例表明，采用该方法具有较快的收敛速度和较高的诊断准确度，说明了该方法的正确性和有效性。
Simulation results of transformer fault diagnosis based on the dissolved gas analysis show that this method improved convergence speed and diagnosis accuracy to some extent and it is effective.
分析了离散时间线性系统模型参数估计误差的收敛性和收敛速度，对参数估计误差服从渐近正态分布的一些条件进行了讨论。
The convergent property and convergent rate of parameter estimation error are analyzed . Some sufficient conditions are given to guarantee the asymptotic normality of parameter estimation error.
分析其收敛性和收敛速度并建立了收敛性理论。
The convergence and the convergent rate were analyzed and some convergent theories were established.
理论分析和计算机模拟均表明，基本的系统模型是成立的，而系数更新的后一种模型有较好的收敛速度。
It is shown analytically and by computer simulations that the basic system model proposed is valid, and that the latter updating model has a faster convergence rate over the former updating model.
接着分析了算法的性能，确保了算法的解的质量和较快的收敛速度。
Then the thesis investigates the performance of algorithm, ensuring that the solution of algorithm has a good quality and the algorithm has a faster convergence speed.
本文分析了逆幂迭代算法的收敛速度。
The convergence of the inverse correlation matrix iteration algorithm is analyzed.
分析了系统稳定性、稳态误差和收敛速度，并在此基础上提出了一种重复控制器频域设计方法。
The stability, static error, and convergence rate are analyzed, and a frequency domain design method is proposed.
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