esprit_tls

怎样看地质图，这本书教给大家看地质图的方法。(How to look at geological map)

用于黑启动求解频率变化值的牛顿拉夫逊潮流分解，输出由每次迭代后各参数的变化量。(Newton Raphson trend for black start solving the frequency change value decomposition, the output from each iteration, each parameter change.)

OFDM_Final_Report.pdf后面附有matlab程序，我猜想可能是老版本matlab，本人进行稍加改造，在matlab环境下打开ofdm.m，执行run即可。原文有两个程序，本人只改造了第一个，第二个仿照改造即可。(OFDM_Final_Report.pdf behind with Matlab procedures, I guess that may be old version Matlab, I conducted a little alteration, In Matlab ofdm.m open environment, the implementation can be run. Original are two procedures, I would only transform the first one, the second will be modeled on the transformation.)

1 swing bus、1 PQ bus、2 transfermor 以matlab劃出結構圖後計算各線路的電流電壓(1 swing bus, 1 PQ bus, 2 transfermor matlab draw diagram after calculation of current and voltage of each line)

这是一个用liblinear进行分类的例子，需要有liblinear环境(Using liblinear to do classification task)

This is a MATLAB based program that computes the weights and beamforming pattern of a: I. Linear array II. Rectangular planar array

说明：  vmd的原始程序，亲测可以用，有什么问题的欢迎大家留言与探讨。(VMD original program, pro test can be used, what questions are welcome to leave a message and discuss.)

说明：  相关向量机（Relevance Vector Machine，简称RVM）是Micnacl E.Tipping于2000年提出的一种与SVM（Support Vector Machine）类似的稀疏概率模型，是一种新的监督学习方法。 它的训练是在贝叶斯框架下进行的，在先验参数的结构下基于主动相关决策理论（automatic relevance determination，简称ARD）来移除不相关的点，从而获得稀疏化的模型。在样本数据的迭代学习过程中，大部分参数的后验分布趋于零，与预测值无关，那些非零参数对应的点被称作相关向量（Relevance Vectors），体现了数据中最核心的特征。同支持向量机相比，相关向量机最大的优点就是极大地减少了核函数的计算量，并且也克服了所选核函数必须满足Mercer条件的缺点。(Relevance Vector Machine (RVM) is a sparse probability model similar to SVM (Support Vector Machine) proposed by Micnacl E. Tipping in 2000. It is a new supervised learning method. Its training is carried out under the Bayesian framework. Under the structure of prior parameters, it is based on Automatic Relevance Determination (ARD) to remove the irrelevant points, so as to obtain the sparse model. In the iterative learning process of sample data, the posterior distribution of most parameters tends to zero, which is independent of the predicted value. The points corresponding to non-zero parameters are called Relevance Vectors, which represent the most core features of the data. Compared with support vector machine, the biggest advantage of correlation vector machine is that it greatly reduces the computation amount of kernel function, and also overcomes the shortcoming that the selected kernel function must meet Mercer's condition.)

说明：  光伏并网逆变器，阳光电源，测试部设计,有待修改 (pv grid inverter,sungrow,test dept desigen)

matlab在数学建模中的应用一书源代码(matlab in the mathematical modeling of a book source code)