matlab-installer-ways

matlab函数，指令集。包括语法和描述(matlab function and instruction set. Including syntax and description)

说明：  非线性问题的线性拟合问题的源程序 非线性问题的线性拟合问题的源程序用MATLAB实现(nonlinear fitting a linear source of the nonlinear fitting the linear source with MAT LAB realization)

Precision/Recall curve drawing.

有限单元法基础(第2版) 配套Matlab源代码(The basis of the finite element method (2))

A sample program to generate the code block segmentation in downlink LTE. This can be used as a reference test vector purposes.

The latest generation of high-end video cards off er considerable computing power using their 100–200 on-card processors, 0.3–1.0+ GB of RAM, and fast inter-processor communications. One promising application of this Graphics Processing Unit (GPU) computing capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU. (The latest generation of high-end video cards offer considerable computing power using their 100-200 on-card processors, 0.3-1.0+ GB of RAM, and fast inter-processor communications. One promising application of this Graphics Processing Unit (GPU) computing capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU.)

matlab newton法，二分法，迭代法，0.618法，进退法(matlab newton law dichotomy, iterative method, 0.618 law, advance and retreat method)

matlab 数字图像处理源代码，需要毕业设计的可以在此处下载(matlab digital image processing source code graduation design is required can be downloaded here)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

说明：  AP聚类算法，亲测可用，可以很快分别不同类别(AP clustering algorithm, pro-test available, can quickly separate different categories)