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某班有N个学生，已知他们参加某次考试的成绩（0~100间的整数），求全班同学的平均成绩。(A class is to have N students, known as their new the result of the examination (0 to 100 between integer),for the whole class average scores.)

joint probabilistic data association with matlab

可以计算不同雷洛系数下的紊流,非常方便!(The main code can compute different turbulence Venturello coefficients, very easy!)

用于脉冲噪声去除的保边缘算法，效果很好，大家可以学习 (Paul edge for impulse noise removal algorithm works well, we can learn)

说明：  可以计算小孔的圆孔的夫琅禾费衍射图和菲涅尔衍射图样(it can calculate the diffraction of small circular)

matlab做的论文资料，从CNKI上找来的，这里免费给大家，希望对大家有用(MATLAB based on the double inverted pendulum control system design method, which died on the CNKI papers, fees, free of charge to everyone here, in the hope that useful)

是帮助初学KALMAN滤波的朋友的入门程序，很有帮助！(is to help novice Kalman filtering friends induction procedures, helpful!)

特徵粹取（feature extraction）是特徵選取（feature selection）的延伸，簡單地說，我們希望將資料群由高維度的空間中投影到低維度的空間，因此，我們必須找出一組基底向量（base）來進行線性座標轉換，使得轉換後的座標，能夠符合某一些特性。 我們可以將特徵粹取分成「包含類別資訊」和「不包含類別資訊」兩大類。包含類別資訊指的是我們已經知道哪些資料分別歸屬於哪一類；而不包含類別資訊的特徵粹取則適用於我們不知道手上的資料點分別該歸屬於哪一類，甚至連該劃分成幾類都不知道的情況。對於這兩大類資料，可以分述如下： 對於「不包含類別資訊」的資料，我們通常使用「主要分量分析」（principal component analysis），簡稱 PCA。 (Cuiqu features (feature extraction) is feature selection (feature selection) extension, simply put, we want to base the projection data the high-dimensional space to low-dimensional space, so we have to find a set of basis vectors ( base) to the linear coordinate conversion, so that after the coordinate conversion, can meet a number of features. We can feature Cuiqu into " category contains information" and " does not contain a category of information," two categories. Contains categories of information refers to what we already know what kind of information are attributed to Cuiqu features include categories of information are not applicable to information we do not know the points are in the hands of the home in which category, and even that is divided into several class do not know the situation. For these two categories of information, can be divided as follows: For information " does not include the categories of information" , we usually use the " )

for engine code, very best cod

一个50行的Matlab有限元程序（二维非线性问题），执行fem2d_nonlinear.m即可。(A 50-line Matlab finite element program (two-dimensional nonlinear problems), the Executive fem2d_nonlinear.m can.)