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A very good introduction about Arithmetic Coding

一个可以直接应用于扩频系统的m序列仿真，m序列具有很好的自相关性，是在扩频系统中应用最广的伪随机码，本程序可以直接在matlab上运行，对于扩频系统的学习有很大帮助。(Can be directly applied to a m-sequence spread spectrum system simulation, m sequences with good autocorrelation in the spread spectrum system, the most widely used pseudo-random code, the program can be run directly in matlab for Spread Spectrum Systems of great help in learning.)

基于无线传感器的matlab工具包·~~~ 还不错~~可以用~~(matlab bag WSNs)

AB公司的ContolLogix 5000软件控制系统编程实例！(AB ContolLogix 5000 software control system programming examples!)

仿冒主用户检测的简答代码，供大家学习交流使用(The short answer to detect counterfeit primary user code , for we learn to use )

多目标环境下 统一数据恒虚警 五种方法 仿真图(Multi-target environment unified data CFAR five methods simulation map)

将信号进行ASK调制 并进行相干和非相干解调 比较误码率(ASK modulation of the signal and the comparison of coherent and incoherent demodulation BER)

This code is about OLA (overlap Addition method) of Digital Signal. First signal is converted into STFT and after that is recovered back to time domain signal using overlap Addition tecnique

说明：  用于路径规划自动寻 基于栅格法的MATLAB程序，后期可以自己加入想要的图形(MATLAB program for automatic search based on grid method for path planning, and you can add your own graphics at a later stage.)

In this paper, we introduce a new machine-learning-based data classification algorithm that is applied to network intrusion detection. The basic task is to classify network activities (in the network log as connection records) as normal or abnormal while minimizing misclassification. Although different classification models have been developed for network intrusion detection, each of them has its strengths and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC (Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both classification rate and run-time efficiency.