Unit-Commitment-Methods-to-Accommodate-High-Level

有限元杆件集成刚度程序，用与计算杆单元刚度矩阵及集成。(beamassemble)

自己写的GA算法，注释写的很完整，初学者可以看一下(GA )

苏金明写的《Matlab图形图像学》，一本学习matlab非常好的书。(SGT written in " Matlab Graphics & Image" , a very good book to learn matlab.)

说明：  运动载体的定位与导航一般应用Kalman滤波算法。可 靠的Kalman滤波算法要求有可靠的函数模型、随机模型以 及合理的估计方法。实际情况中运动载体一般难以确保规 则运动，因而精确的函数模型的构造十分困难。近年来， 有不少学者对机动载体运动模型进行了讨论，所属内容各 具特点，建立的各种模型包括微分多项式模型、常速度模 型、常加速度模型、时间相关模型，半马尔柯夫模型、 Noval统计模型及机动载体的“当前”统计模型(Moving vehicle positioning and navigation general application of the Kalman filter algorithm. Kalman filter algorithm requires a reliable function model, a stochastic model, as well as a reasonable estimation method. Moving carrier in the actual situation is generally difficult to ensure a regular motion, and thus the the precise function model structure is very difficult. In recent years, many scholars have discussed the movement of the motor carrier model, each with distinct characteristics of their respective content, establish various models including the differential polynomial model, constant velocity model, constant acceleration model, time-dependent model, semi-Markov model, Noval statistical model and motor carrier &quot current&quot statistical model)

摩尔边界的源码在计算电磁学中有很大应用，matlab源码，大家好好学习！！！(Moore border in the calculation of electromagnetic source has great application in the study, matlab source, study hard everyone! ! !)

Power Systems Oscillations C4 examples

《MATLAB工程数学》用到的部分程序。(" MATLAB Engineering Mathematics" used part of the program.)

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 " )

说明：  遗传算法优化支持向量机算法,从而更好的提高识别率和预测率(GA-SVM implemented by MATLAB)

现代通信系统使用MATLAB第二版（中英文pdf及所有程序m文件）(Contemporary Communication Systems Using Matlab By:JohnG.Proakis )