ACATSP

这是一个学习matlab很好的教程，里面有很多课件。(this is an usefull materials，it is helpful for matlab learner！)

park变换与park反变换，引入三相正弦输入，在模拟示波器端查看波形，能够得到期望的效果(park and Inv_park)

LS,最小二乘算法，初学者可以很好的应用 (Least-squares algorithm，Applications can be good for beginners)

Numerical optimization, NeaderMead Powell method

用于comsol和matlab直接的二次开发(For comsol and matlab direct secondary development)

说明：  Hardware book for students

说明：  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社，2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性，首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次，它允许指定不同的推理过程，如精确推理和期望传播(EP)。第三，它允许指定似然函数，如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的，允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)

SOME SIMULINK MOTEUR ASYNCHRONE BY BOUZIANE ISMAIL

说明：  对视频序列通过背景减除法进行运动跟踪，里面用到的方法是叠代法(Motion tracking video sequences by background subtraction)

说明：  国外经典电机矢量控制的电子书，内容相当详细(Vector control of foreign e-book classic, is quite detailed )