MATLAB

使用随机方法计算Frobenius模并比较多种逼近方式的误差大小。(Calculating Frobenius norm using random method.)

MIMO系统中采用16QAM调制的ZF、MMSE、ZF-SIC、MMSE-SIC检测(ZF、MMSE、ZF-SIC、MMSE-SIC detection with 16 QAM modulation in MIMO system)

关于普朗克分布的详细讨论。（在mathematica环境下开发）(A detailed discussion of Planck distribution )

基于Matlab的低通滤波器的设计源码，可以通过此代码，模拟低通滤波器的设计。并附有仿真后的图像。(Matlab low pass filter based on the design of source code, can this code, analog low-pass filter design. Together with simulation, the image.)

随着计算机技术的迅速发展和越来越广泛深入地应用于国民经济和社会生活的各个方面，随着 软件系统的规模和复杂性与日俱增，软件的生产成本和软件中存在的缺陷和故障造成的各类损失也 大大增加，甚至会带来灾难性的后果。软件质量问题已成为所有使用软件和开发软件的人关注的焦 点。由于软件是人脑的高度智力化的体现和产品这一特殊性，不同于其他科技和生产领域，因此软件与生俱来就有可能存在着缺陷。(With the rapid development of computer technology and the more extensively used in the national economy and social life in all its aspects, with the growing size and complexity of software systems, software production costs and software defects and faults caused various types of losses also increased significantly, even catastrophic consequences. Software quality has become the focus of all those who use the software and software development concern. Because the software is highly intellectual expression and product of the special nature of the human brain, unlike other areas of technology and production, so the software may be born with a defect exists.)

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 )

用C开发程序时调用Matlab的功能，为精通Matlab编程一书中附带的程序，感觉比较适合初学者。(C development process called Matlab functions, Matlab programming proficiency for a book accompanying procedures, feeling more suitable for beginners.)

hht希尔伯特黄变化的matlab实现不错试过了(hht Hilbert Huang changing tried matlab realize good)

cs压缩感知里的 SP算法，包含说明文档和程序文档(The cs compression perception of the SP algorithm, including documentation and program documentation)

DES加密过程 实现了DES的全部过程 加密算法经典易学(DES Encryption process To achieve the whole process)