ltticeclosedegree

说明：  该code读出naca4412.txt中基本balde坐标，在读取data1.txt中设计要求，生成FinalCoordinates.txt文件，包含所有生成balde airfoil所需coordinates。(this matlab code read the blade coordinates in naca4412.txt, and then read the design requirements in data1.txt. Finally, it will generate the FinlCoordinates.txt which include all the coordinates of blade airfoil.)

solving heat equation

说明：  A comparison between two direct torque control strategies for flux and torque ripple reduction for induction motors drives

this package contain: five matlab function and one script. XOX_OLS: is Common ols regression function that print out results just like Eviews Program. XOX_PanelFix: is Common fix effect panel data regression function that print out results just like Eviews. XOX_PanelRandom: is Common random effect panel data regression function that print out results just like Eviews. XOX_print: is the function for print an matrix in formatted form for panel data results. XOX_FuzzyRegression: is a fuzzy linear regression model function that based on triangle membership function. XOX_ANFIS: is an escript to explain prediction using TAKAGI-SUGENU adaptive neural based inference system.

3D姿态识别的adaboost代码，使用matlab语言编写(A Study of AdaBoost in 3D Gesture Recognition)

Plot coherent SNR improvement versus non-Coherent for different amounts of sample averaging

sim scan software it will help u a lot.......thanks

matlab工具箱的rbf网络用于线性回归和曲线拟合，自己手创，绝非复制(matlab toolbox rbf network for linear regression and curve fitting, creating their own hands, not a copy)

对二维信号进行多尺度离散小波分解，程序运行正常，能够显示小波分解后各频率上的效果图(Two-dimensional discrete wavelet multi-scale signal decomposition, the program is running normally, after the wavelet decomposition can show the effect of the frequency graph)

GM(1,1)模型1-4 1：GM(1,1)模拟模型，在matlab中的输入方法为gm1（x），x指要模拟的序列。 2：GM(1,1)预测模型，在matlab中的输入方法为gm2（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 3：GM(1,1)群模拟模型，在matlab中的输入方法为gm3（x），x指要模拟的序列。 4：GM(1,1)群预测模型，在matlab中的输入方法为gm4（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 gm4对序列趋势比较好的数据预测效果较好，对上下变动的数据，特别是后4个数据趋势跟前面的数据相反的，预测效果很差。 gm2对上下变动的数据，预测效果比gm4好，但对趋势较好的数据，预测精度没有gm4高。 gm3比gm1模拟精度要高。 可以以x=[1 3 5 7 9 11 13 15]进行实验。x输入默认行向量。 所有程序在matlab6.0上调试通过。(GM (1,1) 1-4 1 : GM (1,1) simulation model Matlab in the input method for gm1 (x), x entail simulation sequence. 2 : GM (1,1) model, in the Matlab input method for gm2 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. 3 : GM (1,1)- simulation model, in the Matlab input method for gm3 (x), x entail simulation sequence. 4 : GM (1,1)- forecasting model, in the Matlab input method for gm4 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. Gm4 right sequence relatively good trend data predicted better results, the next change in the data, especially after four data with the previous trend data contrary, predict poor. Gm2 next to the change in forecast resu)