传递熵Matlab

有关协作通信的仿真程序，有助于学习协作通信基础知识。(The simulation program of collaborative communication, help study of collaborative communication infrastructure knowledge.)

matlab处理指纹图像，由于指纹的唯一性、可靠性和稳定性，指纹已成为身份识别和鉴定的一个重 要标志，并被公认为“物证之首”。指纹识别作为一种生物识别技术，历来受到人们的广泛关注和重视，是未来个人身份认证的重要组成部分。(Fingerprint image processing matlab，Because the uniqueness of fingerprints, reliability and stability,fingerprint identification has become an important symbol of appraisal,and is recognized as the "first" material.The fingerprint identified as a kind of biometrics,has received extensive attention of,the individual identity authentication is the important component.Based on the MATLAB software applications for tools,for fingerprint image preprocessing and feature extraction technology research.Including pretreatment part involves by different methods of fingerprint image segmentation to extract valid area,with the improvement of OPTA thinning algorithm for thinning, )

短波跳频信号协议仿真,考虑了 多径的影响,协议传输的准确性(agreement shortwave frequency signal simulation, in consideration of the multi-path effects, the accuracy of transmission agreement)

运用TDOA进行定位的Matlab源代码，(Using TDOA location of the Matlab source code, )

采用一种新的方法对目标进行跟踪，有很好的跟踪精度，可用于军事领域。(Using a new method for target tracking, a very good tracking precision, can be used in the military field.)

1. 图像二值化 2. 边界跟踪，去除离散点 3. 边界提取 4. 删除短边 5. 区分河流与道路 先找到桥梁，利用桥梁上的种子点 对道路进行跟踪，从而提取整条主干道。 (1 image binarization 2boundary tracking, removal of discrete points 3 boundary extraction 4 Remove the short side 5 distinguish rivers and roads the curvature is too large) First find the bridge, the bridge on the use of seed points on the road to follow, thereby extracting the whole trunk.)

说明：  CSF布料滤波算法PYTHON+MATLAB(CSF PYTHON+MATLAB code)

一个很详细的压缩编码，基于MATLAB语言编写的，确实很实用。(A very detailed coding, based on the MATLAB language, is indeed very practical.)

Running a function on several files in Matlab

EMD镜像延拓数据分解，金融数据平稳化过程，有效分解非平稳数据。(EMD decomposition mirror extension data, financial data smoothing process, effectively decompose non-stationary data.)