资源列表
1
- 一个绘制函数图像的程序,可以根据函数来绘制几个图像,便于使用-An image mapping function procedures, according to the function to draw several images, easy to use
plane
- 平面测量的平面控制网程序,可以算得平面控制网上各点的平面坐标和方位角。-The plane control plane measurement procedures can be regarded as plane control line plane coordinates of each point and azimuth.
matlab
- 这是测量的水准程序,便于算出各点的高程和改正数。-This is the standard measurement procedures, to facilitate the elevation of each point is calculated and corrections.
h
- 摄影测量后方交会的程序,采用matlab进行编写,方便大家使用。-Photogrammetric resection procedures, using matlab to prepare, easy to use.
pca0
- 利用主成份分析的方法实现对两类数据的分类处理。代码可直接运行, 有详细注释。-The use of principal component analysis method to realize two types of data classification. Code can be directly run, detailed notes.
PCA_usps
- 利用主成份分析方法实现对usps数据库的分类处理。代码可直接运行, 有详细注释。-Using principal component analysis method for usps database classification. Code can be directly run, detailed notes.
Data-Structures
- 数据结构是计算机存储、组织数据的方式。数据结构是指相互之间存在一种或多种特定关系的数据元素的集合。通常情况下,精心选择的数据结构可以带来更高的运行或者存储效率。数据结构往往同高效的检索算法和索引技术有关。-Data structure is a computer store, organize data. Data structure refers to the mutual relationship between the presence of one or more specific da
pca_iris
- 利用主成份分析方法实现对IRIS数据库的分类处理。代码可直接运行, 有详细注释。-Using principal component analysis method to achieve the IRIS database classification. Code can be directly run, detailed notes.
lda0
- 利用线性判别分析实现对iris数据库的分类。代码可直接运行, 有详细注释。-Using linear discriminant analysis to achieve the classification of iris database. Code can be directly run, detailed notes.
Optimization-Methods-
- 《最优化方法及其Matlab程序设计》较系统地介绍了非线性最优化问题的基本理论和算法,以及主要算法的Matlab程序设计,主要内容包括(精确或非精确)线搜索技术、最速下降法与(修正)牛顿法、共轭梯度法、拟牛顿法、信赖域方法、非线性最小二乘问题的解法、约束优化问题的最优性条件、罚函数法、可行方向法、二次规划问题的解法、序列二次规划法等。-" Optimization Methods and Matlab programming," a more systematic introd
LDA_USPS
- 利用线性判别分析做USPS数据库的分类。代码可直接运行, 有详细注释。-Done using linear discriminant analysis classification USPS database. Code can be directly run, detailed notes.
fisher
- 利用Fisher方法和最近邻分类实现两类数据的分类。可直接运行。-The Fisher method and the nearest neighbor classifier to achieve two kinds of data classification. Can be directly run.
