cengheban

说明：  Ku波段低相噪频率源的研制，KU波段下行转发器发射功率大（大约在100W以上），能量集中，方便接收，，，(the research about Ku)

介绍matlab各种常用命令，让初学者轻松从入门到精通的电子书。(Matlab introduce a variety of commonly used commands, so that easy for beginners from entry to master e-book.)

费希尔线性判别分析代码 Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and -1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem( Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and-1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem)

WIND FRAM CONNECTED WITH GRID

输入一个句子后，通过点击按钮，可以得到本句子的单词个数与句子的个数(Enter a sentence, by clicking on the button, you can get the number of words in this sentence and the number of sentences)

保护最优程序，用matlab编写，适合电力系统从业人员使用。(Optimal protection program , written in matlab, practitioners use for the power system . )

matlab智能算法程序例子，例子中详细介绍了神经网络法遗传算法粒子群算法等解决寻优问题(Examples of intelligent algorithm matlab program, described in detail in the example neural network genetic algorithm particle swarm algorithm to solve the optimization problem)

说明：  包含两个功能的源程序： 1 学生面试问题（如何实现老师面试学生人数的合理规划）。 2 JPDA算法的matlab实现。(The source code contains two functions: a student interview questions (a teacher interview how to achieve a reasonable number of students planning). 2 JPDA algorithm matlab implementation.)

说明：  偏最小二乘法的概述以及MatLAB的程序，非常详细！(An overview of partial least-squares method, as well as MatLAB procedures in great detail!)

首先将测量值与估计值都进行模糊化，然后计算测量值与估计值之间的格贴近度, 利用贴近度来描述各个传感器在测量中的权重，最后得到融合结果。(First, the measured values and estimated values are fuzzified, and then calculated between measured and estimated values of the lattice close to the degree of closeness to describe the use of various sensors in the measurement of weight, and finally get fusion.)