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OFDM的误码率分析，Matlab仿真，希望有用(BER Analysis of OFDM, Matlab simulation, hope helpful)

图像霍特林变换源代码，可实现图像的kl变换(Hotelling transform image source code)

将图象分块(8*8)，作DCT变换，并作IDCT：DCT是一种可分离图象变换，用来图象压缩编码，IDCT用来解压缩。(The image sub-block (8* 8) for the DCT transform, and to make IDCT: DCT is a separable image transformations, is used to image compression coding, IDCT is used to decompress.)

0-1整数规划有很广泛的应用背景，比如指派问题，背包问题等等，实际上TSP问题也是一个0-1问题，当然这些问题都是NP问题，对于规模较大的问题用穷举法是没有办法在可接受的时间内求得最优解的，本程序只不过是一个练习，得意之处是用递归法把所有解都排列出来。另：胡运权所著的《运筹学基础及应用（第三版）》第97页的例3，我用本程序求解得到的结果是：最优解是x*=(1,0, 0, 0, 0)，最优值是f(x*)=8，但书求得最优解是x*=(1,0, 1, 0, 0)，最优值是f(x*)=4，是不是书中写错了，请大家验证。以下是源程序，大家可以任意使用无版权问题，另外，如果大家有大规模的0-1规划的问题也希望提供给我，谢谢。变量个数至少是3个(0-1 Integer Programming is a very broad background, such as assignment, bags and so on. actually TSP is a 0-1, of course, these problems are NP, for larger problem with the law is not exhaustive approach in an acceptable time frame to obtain the optimal solution. this procedure is only one practice, farewell tour is the method used recursive all of the solutions to show. Another : Hu Yun-author of "operational research, and application base (third edition)" Article 97 of the three cases, I use this procedure to solve the result is : is the optimal solution x = (1,0, 0, 0, 0), the optimal values of f (x*) = 8, but the book is to find the optimum solution x = (1,0, 1, 0, 0), the optimal values of f (x*) = 4, the book is not a mistake, please certification. Following is the source)

支持向量机用于训练和分类，包括PCA降维等函数(Support vector machines for training and classification, including functions such as PCA dimension reduction)

The code summerize how to calculate the jitter (RMS) with the incoming signals, such as optical communications and clock and date recovery circuit

matlab编写的square wave的fftbianhuan(matlab prepared square wave of fftbianhuan)

这是一个MIMO信道容量的计算。使用SVD分解和注水定理。(This is a MIMO channel capacity calculations. Using the SVD decomposition and water-filling.)

Collection of Sparse Representation Library(Berkeley+Gatech)

source code for gausian mixture model