matfflab2

The program generates Gold Codes.

最优化算法中的黄金分割法，用于线性寻优过程，算法快速且方便(optimization algorithm gold segmentation method for the linear optimization process, the algorithm is fast and convenient)

说明：  程序用来识别破损的物体，并标注显示。比如在一堆球形的物体中有非球形的物体，可以方便的检测出来，并显示位置(Procedures used to identify damaged objects, and label display. For example, in a pile of spherical objects in non-spherical objects can be easily detected, and the display position)

则卡尔曼滤波的算法流程为： 1.计算预估计协方差矩阵2.计算卡尔曼增益矩阵3.更新估计4.计算更新后估计协防差矩阵(The Kalman filter algorithm processes as follows: 1. Calculate pre-estimate covariance matrix 2 calculate the Kalman gain matrix 3 updated estimate calculated after 4 update estimated defend difference matrix)

关于VC和MATLAB之间建立应用接口的程序，请读者马慢慢平度，标胶都好偶的(On VC and MATLAB interface between the application procedures, the reader is slowly MA Pingdu marked plastic are good duality)

说明：  本文提出一种在原始视频DCT(离散余弦变换)与SVD(奇异值分解)域自适应嵌入水印的算法。算法首先将视频流分割成一个个场景,场景中的视频图像被变换到DCT-SVD域中,水印量化嵌入在最大奇异上,实现了水印盲检测。同时实验证明该算法在满足透明性要求下也满足一定的鲁棒性要求,能够抵抗低通滤波、中值滤波、椒盐噪声、高斯噪声、H.264压缩攻击以及统计攻击和帧剪切等攻击。(This paper presents an original video in the DCT (Discrete Cosine Transform) and SVD (singular value decomposition) algorithm for adaptive watermark embedding. Firstly, a video stream is divided into scenes, scenes of the video image is converted to the DCT-SVD domain, the watermark embedded in the largest singular quantification, the realization of the watermark signal. Furthermore, the experiments show that the algorithm meet the transparency requirements are met under certain robustness requirements, can resist the low-pass filtering, median filtering, salt and pepper noise, Gaussian noise, H.264 compression attacks and attacks and frame shear statistics attack.)

关于小波神经网络的源程序，对研究小波神经网络非常有帮助(on wavelet neural network source, the study wavelet neural network has been very helpful)

Student mini projekt for symulation of regulation temperature in building (Matlab ver)

使用栅格法通过蚁群算法规划机器人全局路径(By using the grid method of ant colony algorithm robot global path planning)

Digital image exercices