math_exp

关于ofdm_qpsk的一些使用小程序 其中包括关于单载波的一些信道干扰影响的比较等(ofdm-qpsk-mycreatechannel11)

k-means算法对irisdata数据集进行聚类(The k-means algorithm clustering the irisdata datasets)

说明：  杂波的一个MATLAB仿真，杂波的产生：先生成一个（0，1）分布的随机数r，让后根据poission分布产生杂波的个数n，这n个杂波是服从均匀分布(Clutter a MATLAB simulation, the resulting clutter: a President (0,1) distribution of the random number r, let poission distributed according to the number of clutter have n, that n is subject to a uniformly distributed clutter)

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)

simulation of uncoded BPSK over AWGN

3d farame analysis , matlab source code

matlabgui matlab 绘图相关教程书内附源码 (matlabgui matlab drawing related code)

以黄锷的EEMD为基础，对信号进行HHT分解，使用时把文件名改为所要处理的数据名称即可(The EEMD Huang E, HHT decomposition of the signal, change the file name to use to be dealt with data name to)

用kalman滤波算法来跟踪鼠标, 小有意思的程序, 有助于理解kalman算法(Using kalman filter algorithm to track the mouse, a small interesting programs, help to understand the kalman algorithm)

This magnitude comparison uses the signless first words and the regular part2 words.