因此，如何获得全局最优的码书成为矢量量化算法设计的主要研究问题之一。
So, how to achieve global optimal codebook become the one of key problems of designing VQ algorithm.
实验结果表明，该算法能够保证求得全局最优解，并且寻优速度有很大提高。
The experiment shows the algorithm can surely and rapidly get global optimum solution and greatly improve con vergence rate.
算法中采用的记忆指导搜索策略重点搜索了各记忆段的局部最优值，避免了全局搜索的盲目性；
The adoption of remembrance-guided search method emphasizes local optimum value in each remembrance segment, which avoids the blindness of global search.
多峰值函数优化结果表明，该算法可以有效地解决早熟收敛问题，更易达到全局最优解。
The optimization result of multi-peak value function shows that the algorithm presented can solve premature convergence problem effectively and converge to the globally optimal solution.
多峰值函数优化结果表明，该算法能更有效地达到全局最优解。
The optimization result of multi-peak value function shows that the algorithm introduced can converge to the globally optimal solution effectively.
现代优化算法主要解决全局最优问题，其本质是概率性的。
The main objective of modern optimization algorithm is to deal with the problem of global optimum, which is essentially probabilistic.
在线性无偏最小方差估计准则下，推导出了该离散化后所得系统的全局最优递推状态估计算法。
In the sense of linear unbiased minimum variance estimation, a global optimal recursive state estimation algorithm for this discretized linear system is proposed.
目前对有约束非线性规划问题还没有通用的求全局最优解的算法。
Currently, there is no general algorithm to find the global optimal solution for the constrained non-linear programming problems.
业已证明，提出的算法可以保证收敛到全局最优解。
It has been proved that the algorithm can converge to globally optimal solution.
高斯·马尔科夫序列实验表明，该算法较好地实现了全局最优，并有助于克服对初始码书较为敏感的缺点。
The experiments of Gauss Markov sequences show that the algorithm has better achieved the global optimal point and helps overcome the shortcoming of the sensitivity to initial codebook.
算例表明，当混沌搜索的次数达到一定数量时，混合优化方法可以保证算法收敛到全局最优解，且计算效率比混沌优化方法有很大提高。
Numerical examples illustrate that the present method possesses both good capability to search global optima and far higher convergence speed than that of chaos optimization method.
仿真表明，本文算法通常都能得到全局最优路径，并且规划速度快、内存需求小，非常适合于实时应用。
Simulation results show that it generates global optimal path in most situations, and is very time and space efficient thus suitable for real time applications.
本文针对一类带有反凸约束的凸函数比式和问题提出了一种求其全局最优解的分支定界算法。
This article presents a branch and bound algorithm for globally solving the sum of convex-convex ratios problem with nonconvex feasible region.
采用线性矩阵不等式技术，将问题转化为一线性凸优化算法，可得问题的全局最优解。
Using the linear matrix inequality (LMI) technique, the problem is converted into a linear convex optimization algorithm so that a global optimization solution is obtained. Finally.
针对一类非线性比式和问题首次提出一种求其全局最优解的单纯形分枝定界算法。
This paper presents for the first time a simplicial branch and bound algorithm for globally solving a class of nonlinear sum of ratios problem.
标准的粒子群优化算法作为一种随机全局搜索算法，因其在种群中传播速度过快，易陷入局部最优解。
The standard particle swarm optimization algorithm as a random global search algorithm, because of its rapid propagation in populations, easily into the local optimal solution.
进化算法作为处理复杂函数最优化、全局最优化和多目标最优化问题的一种有效算法，正日益受到人们的重视。
Evolutionary algorithms are one of the effective algorithms for hard optimization, global optimization and multiobjective optimization problems, which are attached more and more importance to.
算法中的免疫记忆单元确保了快速收敛于全局最优解，算法中的均匀交叉操作则体现了进化的思想。
The immune memory units guarantee this algorithm rapid convergence to global optimum and the uniform crossover operator embody the idea of evolution.
推导了样本熵的近似估计公式，引入最优窗宽、全局最优窗宽的算法，首次解决了样本熵的估计值不惟一的问题。
What is more, the expression for approximately estimating sample entropy is preserced by introducing optimal window-width arithmetic and the overall optimal window-width arithmetic.
与其他混合最优化算法不同的是，该算法没有破坏粒子群和遗传算法的独立性，而是仅通过全局最优样本把两个算法结合在一起。
It selects the optimaler number as a global optimum at every circulation, which makes its result be better than both PSO and GA, then improves the overall performance of the algorithm.
最后利用遗传算法获得威胁网络下的全局最优解。
The global optimal flight path could be obtained by using genetic algorithms.
提供七种最优化算法，三种是全局优化。
Provides seven optimization algorithms, three of which are global.
针对边界约束函数全局最优化和多峰寻优问题，提出一种直接搜索算法。
This paper proposes a direct search algorithm for global optimization and multi-peak searching of functions with boundary constraints.
在理论上，该算法可以获得全局最优解。
Theoretically, the best optimization solution of overall situation can be achieved from the proposed algorithms.
与单点最优算法相比，该方法为多点寻优，单调收敛，可获得全局最优解和用于长、短期或实时优化调度。
The algorithm USES a population of points at a time in contrast to the single point approach by traditional optimization methods. The convergence is monotonic and a global solution is obtained.
该算法本质上是一种随机搜索算法，并能以较大概率收敛到全局最优，特别适用于连续函数的优化。
The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability and be adept in continuous functions optimization.
该算法本质上是一种随机搜索算法，并能以较大概率收敛到全局最优，特别适用于连续函数的优化。
The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability and be adept in continuous functions optimization.
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