dsp1

This an anneal in Matlab

MATLAB 绘图教程对大家会有用的 (MATLAB graphics tutorial would be useful to everyone)

用matlab编写的数字音频水印算法，包括嵌入、攻击、提取(Using matlab digital audio watermarking algorithms, including embedding, attack, extraction)

detail explanation of matlab

产生GPS32颗星的CA码,共包含2个文件,gps_ca_code.m用于产生任一颗星的CA码. Gen32CACode.m用于产生32颗星的CA码(Produce the GPS32 stars of the CA code, consists of two files, gps_ca_code.m CA code used to generate any one star. Gen32CACode.m used to generate the 32 stars of the CA code)

利用磁力计进行姿态估计的程序，用到了欧拉角法和四元数的方法(The use of magnetometers for attitude estimation procedures used in the Euler angle method and quaternion method)

EKF扩展kalman滤波估计二维平面运动轨迹，实现二维平面有源雷达对目标距离和速度的跟踪。(Kalman filtering estimation of 2D motion trajectory EKF extension, realize the planar active radar for target distance and velocity tracking. )

基于稀疏表示的inpaint去水印，部分代码，请安装sparse toolbox....欢迎下载(Camera self-calibration matlab source code, documentation and multi-view geometry ~ ~ and welcome to download the package ....)

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.

在matlab环境下结构模态参数识别，振型、频率都有很高的精度(Structural modal parameter identification in the Matlab environment, have a high frequency modes accuracy)