SA-updata-monituihuo-MATLAB

说明：  能够实现对实验数据的降维，为故障分类做准备(It can reduce the dimension of experimental data and prepare for fault classification)

说明：  一个简单的matlab非线性拟合例子,使用了matlab提供的nlinfit函数.(A simple non-linear fitting matlab example, matlab using the function provided by nlinfit.)

说明，如对听觉神经元间音爆穗间隔（ISI）的刺激之间的重复变异是用来区分标准条件，他们的反应之一。方法使用标准箱及产生的噪声和有偏见的所需数量的估计。此函数计算它到底。 MATLAB的MATLAB的版本7.11（2010b）(Description The variation in Inter-Spike Interval (ISI) between repetitions of a stimulus such as a tone burst for auditory neurons is one of the standard criteria used to classify their responses. The standard method uses bins and produces a noisy and biased estimate of the required quantity. This function calculates it exactly. MATLAB release MATLAB 7.11 (2010b) )

超宽带基础的基本程序,非常不错的小程序,省不少事情啊(the basic procedures, a very good small procedures, many of the things the provincial ah)

jaringan saraf tiruan

说明：  Wireless Sensor Networks WSNs Modified LEACH

matlab实现的k均值聚类算法，可以实现对大量数据的有效分类(matlab implementation of the k-means clustering algorithm, can achieve a large amount of data on an effective classification)

对于二次相位耦合问题高阶谱或高阶统计量的方法是具有明显优势的。谐波相位耦合课程报告实验(Quadratic phase coupling problem for higher-order spectra, or higher-order statistics method is a clear advantage. Harmonic phase coupling courses on the experiment)

matlab simulink教程。适用与matlab的电力系统建模仿真。包括电机，电源，电力电子，和新型电力器件的仿真建模。(matlab simulink)

说明：  分支定界法（branch and bound）是一种求解整数规划问题的最常用算法。这种方法不但可以求解纯整数规划，还可以求解混合整数规划问题。分支定界法是一种搜索与迭代的方法，选择不同的分支变量和子问题进行分支。 对于两个变量的整数规划问题，使用网格的方法有时更为简单。 [1] 通常，把全部可行解空间反复地分割为越来越小的子集，称为分支；并且对每个子集内的解集计算一个目标下界（对于最小值问题），这称为定界。在每次分枝后，凡是界限超出已知可行解集目标值的那些子集不再进一步分枝，这样，许多子集可不予考虑，这称剪枝。这就是分枝定界法的主要思路。(Branch and bound method is one of the most commonly used algorithms to solve integer programming problems. This method can solve not only pure integer programming but also mixed integer programming. Branch and bound algorithm is a method of search and iteration, which selects branches with different branch variables and sub problems. For integer programming problems with two variables, the grid method is sometimes simpler[ 1] Generally, all feasible solution spaces are divided into smaller and smaller subsets repeatedly, which is called bifurcation; And a lower bound of the objective (for the minimum value problem) is calculated for the solution set in each subset, which is called the bound. After each branch, those subsets whose bounds exceed the objective value of the known feasible solution set will not be further branched, so many subsets can not be considered, which is called pruning. This is the main idea of branch and bound method.)