穷举搜索法

穷举搜索法是XPNAV常用且有效的解模糊方法，其不足之处在于复杂度高。

The exhaustive search method is an effective method commonly used , whose shortage is high complexity .

采用一般的穷举搜索法只能搜索到10长的二元互补序列偶。

And only sequence pairs with length below 10 can be got using exhaustive search method .

最简单的块匹配算法是暴力搜索法，也叫穷举搜索法。

The simplest approach dealing patch match is exhaustive search , or called brute-force search .

通过对各种方法计算结果的对比分析，最终确定的计算方法是采用过末点拟合直线、穷举搜索法进行寻优，优化准则是使各拟合直线的相关系数的方差最小。

By comparing the results of various calculation methods , this paper puts forward an optimal calculation method .

其中中间节点法给出了详细的数学证明，穷举搜索法给出了具体的算法。

Middle node law among them give and publish detailed mathematics prove , exhaust and search for law give and produce the concrete algorithm .

并探讨了一些实现网络总长度最短的具体方法，如：中间节点法、距离矩阵法、穷举搜索法、快速评估法。

And probe into some concrete method , namely middle node ,, from matrix law , exhaust law of searching for , assess the law fast .

[过程和方法]采用线性分组、穷举搜索法找到每一个设备参数的最佳线性模型，利用多个模型实现对同一个设备参数进行故障检测。

Using linear dividing into groups and all possible search to obtain a series of optimum linear model for every equipment parameter . Using multi model to realize carrying on the fault detection to same parameter .

提出了首先采用精英保留自适应遗传算法，对浮动瓦块中螺栓杆的位置变量进行连续变量优化，然后采用穷举搜索法，对螺栓杆直径和瓦块厚度进行离散变量优化的递进式优化策略。

Put forward an optimization strategy , first , using elite reserves the adaptive genetic algorithm to topological structure optimization of the location of bolt in the floating panel , then using exhaustive search method to discrete variable optimization of the bolt shank diameter and the panel thickness .

提出了一种线与多边形矢量数据的压缩方法，并在此方法的基础上提出了基于非拓扑关系的穷举搜索压缩法。

A compression method of the line and the polygon vector data is given in this paper . At the foundation of this method , the compression method of the all-list-search which is based on non-topology relation is put forward .

传统的基于穷举搜索的暴力法在攻击密码散列时需要大量的计算，而且往往要经过很长的时间才能完成计算。

To attack password hash , a traditional brute-force method based on exhaustive search need a lot of computing power or a lot of time to complete .