基于matlab的图像素描处理

本人编写的用直方图提取纹理特征的源码，希望对大家有用(I am prepared to use the histogram of the source texture feature extraction, in the hope that useful)

MATLAB软件的解方程函数简介，适合初学者参考(Function of MATLAB software, the solution equation brief reference for beginners)

matlab函数大全，是广大爱好者的极好的学习工具(matlab function Guinness, the vast number of fans an excellent learning tool)

说明：  2D的FDTD程序，有关边界的设定，物理参数的设定等，对学习FDTD很有帮助。(2D of the FDTD program, setting the boundaries, the physical parameters of the set and so helpful in learning FDTD.)

用不同的方法对人体心电信号进行QRS复波检测(QRS complex wave tests on human ECG using different methods)

该程序实现了双变量高斯核密度估计。它可以用于估计双变量概率函数，累积分布函数（CDF）和反演CDF（ICDF）。核密度估计在估计边界区域的时候会出现边界效应。在单变量核密度估计的基础上，可以建立风险价值的预测模型。通过对核密度估计变异系数的加权处理，可以建立不同的风险价值的预测模型。由给定样本点集合求解随机变量的分布密度函数问题是概率统计学的基本问题之一。解决这一问题的方法包括参数估计和非参数估计。参数估计又可分为参数回归分析和参数判别分析。在参数回归分析中，人们假定数据分布符合某种特定的性态，如线性、可化线性或指数性态等，然后在目标函数族中寻找特定的解，即确定回归模型中的未知参数。在参数判别分析中，人们需要假定作为判别依据的、随机取值的数据样本在各个可能的类别中都服从特定的分布。经验和理论说明，参数模型的这种基本假定与实际的物理模型之间常常存在较大的差距，这些方法并非总能取得令人满意的结果。由于上述缺陷，Rosenblatt和Parzen提出了非参数估计方法，即核密度估计方法．由于核密度估计方法不利用有关数据分布的先验知识，对数据分布不附加任何假定，是一种从数据样本本身出发研究数据分布特征的方法，因而，在统计学理论和应用领域均受到高度的重视。

说明：  Kalman算法迭代时对输入信号的跟踪曲线(Kalman algorithm is iterative when the input signal of the tracking curve of)

说明：  Построение ROI изображения

运用matlab编程语言，实现利用Householder变换和Givens变换求解矩阵的QR分解(Use matlab programming language, the realization and the Givens transformations using the Householder transformation matrix QR decomposition to solve)

mcm 论文This is the first in a series of videos that will go through the process of planing and implementation of a simple GUI. Realistically, I would not plan out a GUI this simple, but the idea is to show what my planning process is on a simple example. The purpose of this GUI is to: 1.Select an Excel file and read it into the MATLAB workspace 2.Modify the data that came from the file. In this case by multiplying by a scalar 3.Write the modified data into an Excel file with a name derived from the original filename(mcm outstanding This is the first in a series of videos that will go through the process of planing and implementation of a simple GUI. Realistically, I would not plan out a GUI this simple, but the idea is to show what my planning process is on a simple example. The purpose of this GUI is to: 1.Select an Excel file and read it into the MATLAB workspace 2.Modify the data that came from the file. In this case by multiplying by a scalar 3.Write the modified data into an Excel file with a name derived from the original filename)