ivt

复杂网络中，度分布计算，函数，并绘制出度分布的分布图(Complex networks, distributed computing degree, function, and mapping the distribution of out-degree distribution)

脑电特征提取的典型特征提取算法——共同空间模式方法，本人已亲自调试，并用于论文的写作，是一个提取脑电特征的利器(Eeg feature extraction of typical feature extraction algorithm, joint space model method, I have personally debugging, and used for thesis writing, is a feature extraction of eeg)

一本用于matlab学习的讲义，有助于快速掌握matlab的使用，方便matlab算法的开发(A used in matlab study notes, help to grasp the use of matlab, convenient matlab algorithm development )

电力电子控制系统中使用的12脉波产生仿真模型(power twelvepulses)

二维矩形波导电磁波传播，Matlab程序，实习时编写！(Two-dimensional rectangular waveguide electromagnetic wave propagation, Matlab procedures, internship writing!)

it is code for segment imafe using region growing

基于DQPSK差分编码调制解调,希望对你有帮助。(DQPSK modulation and demodulation based on differential encoding, I hope to help you.)

AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )

这是一个好用的频偏估计算法的matlab仿真程序,基于多相结构的信道化接收机，窗函数法设计一个数字带通FIR滤波器。( This is a useful frequency estimation algorithm matlab simulation program, Channelized receiver based on multi-phase structure, A window function design FIR digital band-pass filter.)

This code is a particle swarm optimization for localization in wireless sensor networks