bianjietiaojian

aiming at the reliability analysis of meaures

MATLAB-SimMechanics机构动态仿真讲解教程(Dynamic simulation of MATLAB-SimMechanics bodies to explain the tutorial)

g729语音编码，MATLAB运行实现，符号国际标准(g729 speech coding, MATLAB runs to achieve, symbol of international standards)

Machine learning in action

模糊熵 神经网络的程序 很有帮助，内容写的很详细。(Fuzzy entropy neural network program is helpful, the content written in great detail.)

老外写的小波变换的工具箱，基于MATLAB环境；压缩包内有详细的说明和相关Demo，参考价值较高。(Written by foreigners Wavelet Toolbox, MATLAB-based environment compressed packet has detailed instructions and Demo, a high reference value.)

基于matlab苹果颜色分级 rgb转hsv(Based on matlab apple color grading rgb to hsv)

adaboost matlab程序 大家可以自己调试看看 欢迎相互学习(adaboost matlab program we can learn from their own debug to see welcome)

串行伪码捕获的简单程序 不含噪声和频移(The serial simple pseudo-code acquisition program free of noise and frequency shift)

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 . )