资源列表
qipanfugaiwenti
- 特殊棋盘覆盖问题，主要是熟悉递归调用过程，把一个大问题转换为若干个相似的小问题，从而递归调用函数解决。-Special board covering problem is familiar with the process of recursive call into a big problem is converted to a small number of similar problems in order to solve the recursive call function.
filtersTest-3.1-2007_10
- 随书源代码 关于人工智能方面的，还可以，供参考。-With the book on artificial intelligence aspects of the source code, but also for information.
avcsr
- 源代码 关于人工智能方面的，还可以，供参考。 -Huawei' s product maintenance materials
SVR
- 在线向量回归分析，有包涵一个例子和内定函数等-On-line vector regression analysis, there is an example of indulgence and unofficially functions, etc.
OnlineSVR_Matlab_2006b_Code
- 在线向量回归分析，有包涵一个例子和内定函数等-On-line vector regression analysis, there is an example of indulgence and unofficially functions, etc.
SearchInComplexNetwork
- 硕士论文。论文对已有的复杂网络搜索策略进行了详细的分析,并重点研究了这些搜索策略在几种典型的复杂网络拓扑结构中的搜索效率-analyze existing search strategies in complex network, and put emphasis on the efficiency of these strategies when searching in complex networks with typical topologies
ComplexNetworkClusteringAlgorithms
- 综述了复杂网络聚类方法的研究背景、研究意义、国内外研究现状以及目前所面临的主要问题,重点分析15 个具有代表性的复杂网络聚类算法-This paper reviews the background, the motivation, the state of arts as well as the main issues of existing works related to discovering network communities, and analyzes/compares 15 ma
81404570LS-SVMlab1.5aw
- 详细讲解了支持向量机的原理及其实现过程，能够很好地理解支持向量机-Explained in detail the principle of support vector machines and its implementation process, can be a good understanding of support vector machines
work
- 包含几个具体事例及其对程序内容的详解，能够帮助理解小波实现得具体过程-Contains several concrete examples of its contents Xiangjie the program can help to understand the specific process may Wavelet
shujujiegou-yanweiminban-quanbudaimashixian
- 数据结构与算法分析（严蔚敏版配套程序实现）-Data Structures and Algorithm Analysis (YAN Wei-min version of complete program implementation)
a_star_pathfinder_v.1.92
- A星路径规划原始演示代码，可以自己设计障碍和起点终点。-A Star path planning the original demo code, you can own design obstacles and end point.
Kalman_Filter
- 学习小波实例，详细叙述了小波分解的原理，是一个很好的例程-Learning wavelet instance, described in detail the principle of wavelet decomposition, is a good routine