Matlab-classical-algorithm

A matlab program, using a image processing. Testing with small images and upload. GO go go.

本算法在Matlab2008b 环境下实现了立体视觉中摄像机的基础矩阵计算。包括main, sevenPoint、eightpoint 和eightpoint_norm三个函数。 main.m 是程序的入口，包括生成和读入实验数据，分别调用sevenPoint、eightpoint 和eightpoint_norm 三个函数求基础矩阵，最后绘制出最后的结果。sevenPoint.m 是用7 点法求解基础矩阵。eightpoint.m 是用8 点法求解基础矩阵，eightpoint_norm.m 是数据规格化后的8 点法求解基础矩阵。(The algorithm is implemented in Matlab2008b environment based stereo vision camera matrix calculations. Including the main, sevenPoint, eightpoint and eightpoint_norm three functions. main.m is the entry, including the generation and reading test data were calling sevenPoint, eightpoint and eightpoint_norm three fundamental matrix function evaluation, and finally draw the final result. sevenPoint.m 7 method is based on matrix. eightpoint.m 8-point method is based on matrix, eightpoint_norm.m the data after the 8-bit normalized fundamental matrix method. )

Another good file for nothing

This file is simulation of Active Power in matlab simulink. This file is helpful for understanding FACTS.

Dirty paper trellis code for watermarking

说明：  固高公司的三自由度直升飞机的神经网络控制的自校正控制方法2(solid high degree of freedom of three helicopters of the neural network to control self-tuning control method 2)

这是用身高体重数据进行性别分类的实验。 用最小错误率贝叶斯分类器决策时，首先通过比较概率大小判断一个体重身高二维向量代表的人是男是女，然后再逐一与已知性别的数据比较，就可以得到错误率的统计。然后改变先验概率，重复上面的过程，观察数据结果的变化。 用最小风险贝叶斯分类器决策时，首先求出用最小错误率贝叶斯分类器得到的条件概率；然后根据人为给定的决策表，根据公式算出条件风险；然后逐一比较条件风险，找出使条件风险最小的决策（也就是分类）。最后用分类得到的结果逐一比较已经知道的原始数据，统计处错误率。 (This is the height and weight data for gender classification experiment. With the minimum error rate Bayesian classifier decisions , first by comparing the probability of the size and weight to height to determine a person represented by two-dimensional vector is male or female , and then one by one with known gender data comparison, the statistical error rate can be . Then change the prior probability , repeat the above process , the results of the changes observed data . Bayesian classifier with the minimum risk decision-making , first find the minimum error rate using Bayesian classifier to get the conditional probability then artificially given decision table , according to the formula to calculate conditional risk and then one by one more conditional risk , to find ambassador to the conditions of minimum risk decision making (ie classification) . Finally, the results obtained with the classification by-side comparison of the raw data have been aware of SD error rate . )

This file is very important for student ....

船舶simulink仿真模型包括螺旋桨等(ship simulink)

to reference a a dlg using Matlab code, this can realy help you.