IPAL-master

SOM-SVM模型是利用SOM的聚类特点，将含有相同特征的输入样本聚集在一起，并把离聚类中心较远的输入样本舍去。经过20%的样本压缩后，将含有代表性的小样本再送入SVM进行训练。本文的样本集通过实验平台采集，验证了基于支持向量机的频谱感知方法在实际数据测试条件下也能取得很好的感知性能。仿真结果表明，SOM-SVM模型在低信噪比下，频谱检测率接近100%，检测错误率也得到了很好的改善。(The SOM-SVM model is based on clustering characteristics of SOM, the input sample will contain the same features together, and the input samples from far down the clustering center. After 20% samples were compressed, the representative samples were sent to SVM for training. In this paper, the sample set is collected through the experimental platform, and the spectrum sensing method based on support vector machine is proved to be able to achieve good perception performance under the actual data testing conditions. The simulation results show that the detection rate of SOM-SVM model is close to 100% at low SNR, and the detection error rate is also improved.)

说明：  LibMPSSE-I2C_source.zip, ft232x转I2C代码(LibMPSSE-I2C_source.zip, Ft232x to I2C code)

该文章属于计算机视觉领域，它主要论述了在运动目标分析中如何去除影子和半影的影响，该文章所涉及的方法应用较广泛且算法简单，是一篇不可多得文章-this paper is good,it s tell us how to remove shadow and umper,the method is used in moving object detection

builds an alternate memory allocation scheme into ToyFDTD1. Contributed by John Schneider, it guarantees that the data arrays are contiguous, which the ToyFDTD1 scheme does not. Released 6 December, 1999.

一个非常好的智力游戏，教学用自学用斗形，才数字-A very good mental game, teaching a self-learning bucket-shaped, only the number of

步进电机控制，直流电机控制，加法器，状态机等等经典的VHDL例子程序。-Stepper motor control, DC motor control, adders, state machines, etc. The classic example VHDL procedures.

C# 改变屏幕分辨率，功能仿windows 的屏幕分辨率设置，改变滑块改变分辨率大校本例可学习一下滑块的用法。源代码如下： 　　long RetVal = 0; 　　DEVMODE dm = new DEVMODE(); 　　dm.dmSize = (short)Marshal.SizeOf(typeof(DEVMODE)); 　　dm.dmPelsWidth = dWidth;//宽 　　dm.dmPelsHeight = dHeight;//高 　　dm.dmDisplayFrequency = 85;//刷新率 　　dm.dmFields = DEVMODE.DM_PELSWIDTH | DEVMODE.DM_PELSHEIGHT | DEVMODE.DM_DISPLAYFREQUENCY | DEVMODE.DM_BITSPERPEL; 　　RetVal = ChangeDisplaySettings(ref dm, 0);

ct952 source code use for Digital Frame Photo

说明：  在有风和无风条件下对气体污染扩散的分析和模拟(Analysis and Simulation of Gas Pollution Diffusion under Wind and No Wind Conditions)

说明：  灰色系统GM（1,1）模型，用于预测分析，简单易懂，条理清晰(Grey System GM(1,1) Model for Prediction and Analysis, Simple and Clear)