The image is split into several blocks , and every block is processed individually . so we can get ride of solving large linear equations and calculating huge matrix , and the time and space complexity are lowered greatly 该方法按照图像极值点的分布将图像划分成若干块,分块处理,避免了求解大型线性方程组以及大矩阵产生,较好地降低了时间复杂度和空间复杂度。
Cipher can only be decoded in the terminal . because computation of the rijndael only needs a little of memory , so it is proper for cooperative product ’ s data to encrypt in the terminal whose hardware is limited . all programs are written in c / c + + language in linux and 由于各种攻击rijndael加密算法的时间和空间复杂度都非常大,使破译这种加密算法密钥的难度极大,所以采用rijndael加密算法对外协产品数据进行加解密具有非常高的安全性。
The whole work in this paper is listed as followed : firstly , this paper set forth on management of spatial data and general mining process in spatial data mining ; secondly , the deficiency of gis spatial query on the database and the necessity of data ming are referred to and the source data is preprocessed ; thirdly , the single - dimension table is discussed including three parts : the theory of rough is talked about and is used to analyze the preprocessed data . also , the data is disposed by programming ; the disadvantages of the apriori algorithm are referred to . based on the original algorithm , advaced _ apriori algorithm is put forward to by perfecting the apriori algorithm 对rough集理论算法思想进行了论述，并编程实现了对gis属性数据的处理；讨论关联规则，指出了apriori算法的不足，在原算法的基础上改进了算法；与原算法对比， advanced _ apriori算法在算法复杂度(空间复杂度与时间复杂度)上具有很大的优越性；给出这三种方法( rough集理论、 apriori算法、 advanced _ apriori算法)在算法复杂度(时间复杂度和空间复杂度)的比较，并对优劣进行评定； 4 、多维表的处理：提出空间数据挖掘模型，采用sqlserver建立星形数据模式，以此建立空间数据立方体，采用dbminer进行数据挖掘； 5 、最后是本文的结论和展望；对前面各章的总结，得出几点结论，并指出需要进一步探讨的问题。
In the information gathering research , the paper uses " redundancy webpage filtering system " to show how to resolve the reconstruction problem in the information gathering process . the paper mainly discussed how to reduce the time complicacy and space complicacy of the filtering system 在信息资源建设方面，本文用“冗余网页过滤系统”来说明如何解决资源建设中的重复建设问题，在研究中主要针对算法的时间复杂度和空间复杂度进行了优化，找到了表达一篇文档的最优特征项个数数值，在确保正确率的基础上加快过滤速度。
Random sort is often applied in analysis and simulation of digital signal processing , and its algorithm affects the computation efficiency . in this paper , optimal algorithms are put forward , and can greatly reduce space and time complexity degree of previous algorithms . both theoretic analysis and experimental simulation prove that optimal algorithms can efficiently promote the computation efficiency and save memory 随机排序经常出现在数字信号处理的分析和仿真中，尤其用于交织器的比较分析和优化设计中，它的算法优劣直接影响到计算仿真的效率.针对原有算法，本文提出了优化算法，大大改善它的时间和空间复杂度.定量的理论分析和实际的仿真测试都表明，优化算法能够有效提高计算效率和节省存储空间
The optimized feature set feeds a 3 - class classification module , which is based on the traditional binary svm classifier . and the proposed linear programming svm reduces the burden of the svm classifier and improves its learning speed and classification accuracy . a new algorithm that combined svm with k nearest neighbor ( knn ) is presented and it comes into being a new classifier , which can not only improve the accuracy compared to sole svm , but also better solve the problem of selecting the parameter of kernel function for svm 在研究了数据挖掘、支持向量机及其有关技术的基础上，建立了实现三类水中目标识别的svm方法；采用线性规划svm解决了传统二次规划svm在海量样本情况下导致的时间和空间复杂度问题；提出了将最近邻分类与支持向量机分类相结合的svm - knn分类器应用于水中目标识别的思想，较好地解决了应用支持向量机分类时核函数参数的选择问题，取得了更高的分类准确率。
