zishiyingGA

Absorbing Boundary Conditions in Free Space

采用MUSIC方法的白噪声频率检测仿真 白噪声中单个正弦信号的频率检测与估计 白噪声中多个正弦信号的频率检测与估计 (MUSIC method using white noise white noise simulation of the frequency of detection of a single frequency sinusoidal signal detection and estimation of white noise in the frequency of a number of sinusoidal signal detection and estimation)

now some matlab code for fem is here.pls download it

介绍matlab优化工具箱，举了很多有代表性的例子(Matlab optimization toolbox introduced, cited many examples of representative)

说明：  相位解包裹.我们可以从中获取波免从干涉图中(Phase unwrapping. From which we can get free from the interference pattern of wave)

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.)

一个100*100的正方形，用半径为10的圆覆盖，随机在100*100的平面内放置圆心，问至少需要多少个圆，才能使得成功覆盖整个区域的概率在95 以上？并给出一个均匀随机放置装置的分布图。(A 100* 100 square, a circle with a radius of 10 covers, 100* 100 randomly placed on the center plane, and asked how many circles at least, to cover the entire area so the probability of success of 95 or more? And gives a uniform distribution of randomly placed devices.)

GMSK的matlab实现。在matlab环境下实现GMSK的调制与解调。(The matlab implementation of GMSK)

TDOA定位算法，用于实现无线定位中的TAYLOR算法(TDOA location algorithm for wireless location algorithm TAYLOR)

code for cancer cell classification using template based learing based on TEMPLAR