Q-learning

solve power flows by gauss seidel method ans newton Rapson

Recursive Least Squares.

支持向量机是用于分类与回归的技术。由于其自身的诸多缺点，如无法获得概率输出，需要估计一个误 差参数C，以及必须使用Mercer 核函数等。相关向量机算法，克服了SVM 上述缺点，RVM 能获得与SVM 相比拟的推 广性能，并且更为稀疏。在此基础上，文中介绍了一种RVM 回归用于分类的新分类方法，用RVRC 来表示。并通过 实验证明了它的可行性。(Support vector machines for classification and regression techniques. Due to its many shortcomings, such as the probability that the output can not be obtained, need to estimate an error parameter C, and the need to use Mercer kernel function and so on. Relevance vector machine algorithm to overcome these shortcomings of SVM, RVM and SVM can be obtained comparable to promote performance and more sparse. On this basis, the paper introduces a RVM regression was used to classify new classification method, RVRC to represent. And through experiments proved its feasibility.)

智能天线小程序，计算电流分布，方向图等等对初学者有帮助(smart antenna， easy for junier learner)

this is matlab version of removal of noise

matlab，GUI，界面设计，新手入门(matlab, GUI, interface design, Getting Started)

Rossler混沌系统加入控制器后，在控制器作用下在有限时间内仍然达到了镇定(Rossler chaotic system to join the controller after the controller under a limited period of time still to reach a calm)

　　在目前的人脸图像信息处理领域中，包含有人脸识别、人脸跟踪、姿态估计、表情识别等多个研究方向，然而，所有这些研究方向都涉及到一个人脸标识和定位的问题，即必须知道人脸在图像中的位置以及尺寸——人脸检测。因此，对于一个完整的、自动的人脸信息分析系统来说，人脸检测算法是必不可少的。本文主要是对基于matlab平台的彩色图像皮肤区域分割算法及人脸检测系统的设计做了介绍。(In the face image information processing, including face recognition, face tracking, pose estimation, expression recognition research direction, however, all of these studies are related to the direction of a person the face identify and locate the problem, that is,You must know the position of the face in the image and size- face detection. Therefore, for a complete automatic face information analysis system, the face detection algorithm is essential. This paper introduced the design of the matlab platform based on the area of ​ ​ skin of color image segmentation algorithm and face detection system.)

基准测试函数中的griewank函数代码(Griewank test function in the function code)

是LBP突破级别的始祖性文章，来自图像处理与计算机视觉领域最顶级的期刊PAMI，是大家学习LBP的一个最好文章(a best paper for lbp PAMI)