arbiter

finite difference method with Crank-Nikolson approach(SOR) for American call option

利用gmm模型进行特征分析的程序，欢迎与各位相关研究的朋友进行交流(use gmm model analysis procedures, and welcome to friends from the relevant research exchange)

信号与系统基础知识包括连续信号与模型、离散信号与模型；常用信号变换包括Z变换、(Basic knowledge of signals and systems, including continuous signal with the model, discrete signals and model common signal transform including Z transform,)

gabor变换——gabor变换能有效的一直字符的噪声，变形、断裂、模糊以及亮度不均匀图像干扰(gabor)

质心加权算法质心加权算法质心加权算法质心加权算法(Weighted centroid algorithm weighted centroid algorithm weighted centroid algorithm weighted centroid algorithm)

TE（田纳西-伊斯曼）系统的源代码，对故障诊断仿真具有一定的意义(TE (Tennessee- Eastman) system source code, simulation of fault diagnosis of some significance)

介绍线性预测编码(LPC)及其基本原理，由语音信号常用的全极点模型的传递函数推导出线性预测方程，(Introduction of linear predictive coding (LPC) and the basic principles of commonly used by the speech signal transfer function of all-pole model of a linear prediction equation is derived,)

三维点云法向量估计综述由于获取方便、表示简单、灵活等优势，点云逐渐成为常用的三维模型表示方法之一。法向量作为点云必不可少的属性 之一，其估计方法在点云处理中具有重要的位置。另一方面，由于点云获取过程中不可避免的噪声、误差和遮挡，点云中通常含 有噪声、外点和空洞，并且部分采样模型如CAD模型，也会存在尖锐特征，这些都给法向量估计提出了挑战。对当前已有的点云 法向量估计算法进行综述，分析其原理及关键技术，着重分析它们在处理噪声、外点和尖锐特征等方面的能力并给出比较，最后 为未来研究提供了一些建议(The three-dimensional point cloud normal vector estimation summarized obtain convenient, represents a simple, flexible, and becoming one of the methods commonly used three-dimensional model represents the point cloud. Normal vector of one of the as point clouds essential attributes, its estimation method has important position in the point cloud processing. On the other hand, the noise is inevitable in the process to obtain because of the point cloud, error and occlusion, point cloud typically contains noise outside point and empty, and part of the sampling model such as CAD models, there will still be sharp features, which gave the normal vector estimated that presents a challenge. Overview of current existing point cloud normal vector estimation algorithm, analysis of the principle and key technologies, and analyzed their ability to deal with the noise, the outer points and sharp features and gives comparison, and finally provide some suggestions for future research)

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广义最小方差自校正控制（间接算法）MATLAB仿真程序，有注释(Generalized minimum variance self-tuning control (indirect method) MATLAB simulation program, there are comments)