testCRC8

MATLAB数据可视化算法教程MATLAB data visualization algorithm tutorial(MATLAB data visualization algorithm tutorial MATLAB data visualization algorithm tutorial)

我用C#实现的一个双边滤波器，使用unsafe代码，用指针获取像素。(I use C# to achieve a bilateral filter, use unsafe code to get pixel pointer.)

用MATLAB仿真瑞利信道下的BPSK系统的误码率 和信噪比的关系曲线。(Using MATLAB simulation under Rayleigh channel BER BPSK system and the relationship between the curves of signal to noise ratio.)

matlab的入门程序，包含图像处理模块(matlab for the young,including the image recognition modules)

图论中关于最短路径的Dijkstra算法和通过两指定顶点的最短路径算法。(The shortest path on graph theory and the Dijkstra algorithm specified by two vertices of the shortest path algorithm.)

程序主要是求一段音频数据的基音频率 jiyinzhouqi.m --------求基音周期 find_maxn.m --------求自相关函数的最大值 test2.wav --------程序中用到的示例wav数据文件(The program is mainly the fundamental frequency for an audio data Jiyinzhouqi.m- for pitch period Find_maxn.m- the maximum value of autocorrelation function Test2.wav: the procedures used in the example of wav data file)

以人体步行运动为研究对象，通过构造人体几何和运动模型(Using human ambulation as the research object，by constructing human geometrical and kinetic model)

说明：  实现ASK调制的详细过程，对学习很有帮助(ASK modulation to achieve the detailed process of learning is helpful)

matlab编写的视频关键帧提取程序，可自动从视频中提取帧，提取第几帧可在程序中自行设定，另附有批量处理视频的主函数。(matlab prepared video key frame extraction procedures can be automatically extracted from video frames to extract the first few frames can be set in the program, batch processing video attached with the main function.)

RNNSIM ver. 1.0 is a program with an intercative graphical user interface (GUI) that runs under MATLAB ver. 5.0 or higher. The program can be used in training and testing the Random Neural Network(RNN) models. This version (ver. 1.0) implements only the 3 layer feed forward RNN model. In the next versions, the multi hidden layers and the recurrent RNN models can be implemented. To obtain faster training, the training section can be written as a MEX file and invoked from the GUI. If you have the m files in the directory rnnsim for example, then you can run the program following the next steps: 1- run MATLAB as usual 2- from the MATLAB command window, write cd rnnsim 3- from the MATLAB command window, write rnnsim