draw

principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called eigenfaces, which can be considered as points in a linear subspace called “face space” or “eigenspace”

用matlab进行多聚焦图像融合，包括图像直接融合，傅里叶变换融合，和小波融合的源代码( multi-focus image fusion by matlab, including direct images fusion, Fourier transform integration, and wavelet fusion )

说明：  能够实现模型预测功率控制，提高直接功率控制的稳态以及动态性能(It can realize model predictive power control and improve the steady-state and dynamic performance of direct power control)

说明：  采用最新的人工智能算法，对城市问题（tsp）问题进行了很好的解决(Using the latest artificial intelligence algorithms, to urban problems (tsp) had a very good problem to solve)

详细介绍了MATLAB的基础，并结合实例讲解了其应用(Details of the basis of MATLAB and explain with examples of its application)

Strategic Management

将Quaternion四元素坐标系转换为一般的欧拉角坐标系，避免采用反三角函数导致的值域限制问题。参数xi为搜索的精度，对于每个欧拉角可以分别设定，xi越小，搜索越精确。(Quaternion quaternion coordinate system will be converted to general Euler angle coordinate system, avoiding the use of inverse trigonometric functions due to range limitations. The accuracy of the search parameter xi, for each Euler angle can be set separately, xi smaller, more accurate search.)

nothing is impossible

Create some artificial two-term mixture data

说明：  高等光学仿真-光波导、激光书中的部分程序代码(Higher optical simulation- optical waveguide laser book code)