T-test

可以实现CIEDE2000,CIEDE94,CIEDE1976,CMC,LAB值计算(compute CIEDE2000,CIEDE94,CIEDE1976,CMC,LAB)

说明：  Mobile Robot Simulation by Matlab

求矩阵的逆阵，利用高斯消去法，是本人编写的MATLAB源码(Inverse matrix array, the use of Gaussian elimination is, I prepared MATLAB source)

用matlab来生成全息图的一个样例程序。简单实用(Using matlab to generate a sample program hologram. Simple and practical)

涵盖了MATLAB多种常用的数学函数，包括：基本数学函数，MATLAB常用的三角函数，MATLAB的永久常数，MATLAB基本绘图函数等。(Covers a variety of commonly used MATLAB mathematical functions, including: basic mathematical functions, MATLAB used the trigonometric functions, MATLAB permanent constant, MATLAB and other basic drawing functions.)

单项逆变simulink仿真模型，成功测试。(Single inverter simulink simulation model, and successfully tested.)

说明：  咬尾卷积码的MATLAB代码，讲的非常详细和深入(Biting tail convolutional code matlab code, said very detailed and in-depth)

自己编的一个雷达面显示程序，主要练习的是划线函数的使用技巧(radar,for fun,)

Bandpass filter program.

NP是美国匹兹堡大学的T.L.Saaty 教授于1996年提出了一种适应非独立的递阶层次结构的决策方法，它是在网络分析法（AHP）基础上发展而形成的一种新的实用决策方法。其关键步骤有以下几个： 1 确定因素，并建立网络层和控制层模型。 2 创建比较矩阵。 3 按照指标类型针对每列进行规范化。 4 求出每个比较矩阵的最大特征值和对应的特征向量。 5 一致性检验。如果不满足，则调整相应的比较矩阵中的元素。 6 将各个特征向量单位化(归一化)，组成判断矩阵。 7 将控制层的判断矩阵和网络层的判断矩阵相乘，得到加权超矩阵。 8 将加权超矩阵单位化(归一化)，求其K次幂收敛时的矩阵。其中第j列就是网络层中各元素对于元素j的极限排序向量。 (NP is a professor at the University of Pittsburgh TLSaaty presented in 1996, an adaptation of non-independent Hierarchy of decision-making method, which is the analytic network process (AHP) formed on the basis of the development of a new and practical decision-making method . The key steps are the following: A determining factor, and a network layer and control layer model. 2 create a comparison matrix. For each of the three types of indicators in accordance with normalized columns. 4 find the maximum for each comparison matrix eigenvalue and the corresponding eigenvectors. 5 consistency test. If not satisfied, then the comparison to adjust the corresponding matrix elements. 6 will each feature vector units of (normalized), to determine the composition of matrix. 7 to determine the control layer and network layer to determine matrix matrix multiplication, to be weighted super-matrix. 8 of the weighted super-matrix units of (normalized), seeking the powe)