doublePWMforwindpower

Cyranose@320便携式电子鼻的检测数据,对象是中药材.在MATLAB上进上气味指纹图谱的分析,其4品种的中药材.结果表明其能将其完全分类.(Cyranose @ 320 portable electronic nose detection data, is of Chinese herbal medicines. In progress on MATLAB odor fingerprint analysis, the 4 species of Chinese herbal medicines. The results show that its able to complete classification.)

code for Color Quantization

It is related to image processing

一种噪声辅助数据分析方法,基于人工神经网络的常用数字信号调制，信号维数的估计。( A noise auxiliary data analysis method, The commonly used digital signal modulation based on artificial neural network, Signal dimension estimates.)

利用朴实贝叶斯方法求解有关肺炎的问题。肺炎对应有四个特征：发烧、疼痛、咳嗽和血细胞异常，当确定了患肺炎与否时，四个特征条件独立。假设患肺炎与否和四个特征都可表示为Ture和False。 根据pneumonia.tex文件中的数据（500行，每行前4个数对应4个特征变量，第5个数对应患肺炎是否为真，以0表示False，1表示Ture），编写Matlab 程序 maininference.m，从example.txt中读取病人的症状信息（0表示False，1表示True，-1表示not given），并计算对应的患肺炎的可能性。所给的信息按发烧、疼痛、咳嗽、血细胞异常的顺序排列。将计算结果保存在answer.txt中。(Simple Bayesian method to solve the question of pneumonia. Pneumonia corresponding four characteristics: fever, pain, cough and blood cell abnormalities, determine the risk of pneumonia or not, the four characteristics of conditional independence. Assumptions suffering from pneumonia or not and four features can be represented as Ture and False. According to the data pneumonia.tex file (500 lines, each line of the first four numbers corresponding to the four characteristic variables, number 5 corresponds to the risk of pneumonia is true, 0 represents False, said Ture), to write Matlab program maininference. m from example.txt read the information of the patient' s symptoms (0 = False, said True, the-1 indicates not given), and to calculate corresponding to the likelihood of suffering from pneumonia. The information given by the order of fever, pain, cough, blood cell abnormalities. The calculated results is be saved in answer.txt.)

matlab下的bwmorph程序,希望能给大家带来帮助.(Matlab under bwmorph procedures in the hope that we can bring to help.)

maven seetingmaven seetingmaven seetingmaven seeting(maven seetingmaven seetingmaven seetingmaven seetingmaven seetingmaven seeting)

计算正弦信号加噪声的相关函数。系数b 决定余弦相关函数在噪声指数型相关函数中的“比重”。T为正弦信号周期。正弦信号加相关噪声的相关函数图像为一个指数函数和一个余弦函数叠加的波形。(Calculated sinusoidal signal plus noise correlation function. Coefficient b determine the cosine correlation function in the noise correlation function of exponential type in " proportion." T for the sinusoidal signal cycle. Sinusoidal signal plus noise correlation function related to the image as an index function and a cosine function superimposed waveform.)

学习MATLAB7.0经典英文教材，帮助相关开发人员学习MATLAB7.0的使用。(MATLAB7.0 classic English learning materials to help developers learn MATLAB7.0 related use.)

MATLAB下的音频AGC实现 (MATLAB audio AGC )