ARQ

分解结构振动模态,识别模态参数，将多自由度振动分解为若干单自由度振动的叠加(structural mode decomposition)

说明：  TCP-AQm router design active queue management

对编码中的16QAM编码方式进行仿真，很简单的，绝对可以运行(The 16QAM coding for coding the simulation, a very simple, absolutely you can run)

信号处理中关于多速率转换的matlab源程序。(Signal processing, multi-rate conversion on matlab source.)

EOF（经验正交函数分解）可以进行时空分离，同时也可以分析周期规律(EOF (empirical orthogonal function decomposition) can be temporal separation, but also can analyze cycle regularity)

TH-ppm模板.计算PPM—TH—UMB相关掩模(TH-PPM mask)

二维TM波传播，使用matlab进行仿真(2D-fdtd matlab simulation)

卷积码的维特比译码仿真，基于MATLAB的一种源代码，很实用的(Convolutional code Viterbi Decoder Simulation)

关于瑞利信道，莱斯信道等的仿真源代码，比较准备，贴近理论(On Rayleigh channels, Rice channel simulation source code, etc., more preparation, close to the theoretical)

ROC curves illustrate performance on a binary classification problem where classification is based on simply thresholding a set of scores at varying levels. Lenient thresholds give high sensitivity but low specificity, strict thresholds give high specificity but low sensitivity the ROC curve plots this trade-off over a range of thresholds (usually with sens vs 1-spec, but I prefer sens vs spec this code gives you the option). It is theoretically possible to operate anywhere on the convex hull of an ROC curve, so this is plotted too. The area under the curve (AUC) for a ROC plot is a measure of overall accuracy, and the area under the ROCCH is a kind of upper bound on what might be achievable with a weighted combination of differently thresholded results from the given classifier