Mesh2d-v24

已知一个序列x(n)=0.5cos(0.55*pi*n)+cos(0.45*pi*n),时域FFT分析其频谱。 （1）使用不同宽度的矩形窗截断该序列为M点，取M分别为：20，40，160,观察不同长度对频谱影响；（2）使用哈明窗和凯泽窗重做；（3）对三种窗的结果进行分析比较；（4）总结窗类型和长度对频谱分析的影响。 (Known a sequence x (n) = 0.5cos (0.55* pi* n)+ Cos (0.45* pi* n), time-domain FFT analysis of its spectrum. (1) use a different width of the rectangular window of the sequence for M cut-off point, take M are as follows: 20,40,160, observing the impact of different lengths of the spectrum (2) the use of Hamming window and the Kaiser window redo (3 ) on the three windows analyzed and compared the results (4) summarize the type and length of window for spectrum analysis.)

在立体空间中绘制八面体的Matlab源程序，并对该八面体进行分类(Draw octahedral Matlab source in three-dimensional space and classify the octahedral)

jackknifing 平行因子分析模型 （不需要多维数据的工具箱）(Jackknifing of PARAFAC models- Version 2.03- self-contained (no need for the Nway Toolbox))

controle indépendant des puissances active et réactive de la MADA (DFIG)

a self- embedding block wise fragile watermarking scheme with tamper detection and content recovery capability. The proposed scheme embeds the shuffled extensive ten bit Recovery data and two bit Authentication data of the image block into the least significant bits (LSB) of its corresponding mapping block.The integrity of a test block is decided by comparing 2×2 non overlapping block of the test block with its corresponding mapping block. Experimental results show that the suggested scheme outperforms conventional self recovery fragile watermarking algorithms in alteration detection as well as in tamper recovery of the image.

运用非负矩阵分解算法分解原始数据矩阵，得到基矩阵和系数矩阵，并用于信号分离。(The non-negative matrix decomposition algorithm is used to decompose the original data matrix, and the base matrix and coefficient matrix are obtained.)

MATLAB编程书籍,适合于刚开始学习的用户.(MATLAB programming books, suitable for beginning to learn the user.)

自己编写的对一幅图像实现最近邻插值和双线性插值，可以直接运行，效果很好。(Write your own images of a nearest neighbor interpolation and bilinear interpolation, can be run directly, the effect is very good.)

part 5 schrodinger solve...

说明：  侯媛彬 神经网络 西安电子科技大学出版社 全书程序夹CH11(Neural network)