扩频与解扩

tells the spots to open and to flag in a 5*5 minesweeper(needs to be called again and again) can be expanded for bigger minesweeper games easily

说明：   非线形回归分析的matlab源代码和文本分析的文档.(Non-linear regression analysis matlab source code and text analysis of documents.)

full implementation to LDA with Minumum distance Classifier for face recognition and easy to implement.

Das Stundenbuch ueber Fehrs

Mallat 卷积实现,破解matlab自带程序,其结果一样.希望对大家有帮助.(Mallat convolution implementation, crack matlab own procedures, the same result. Want to help everyone.)

這是一個 Matlab的（和獨立應用）端口的出色的機器學習算法，隨機森林` - 由Leo布賴曼等。從 R -源由Andy鴻等。 http://cran.r-project.org/web/packages/randomForest/index.html（Fortran的原由Leo布賴曼和Adele卡特勒，研究港口安迪鴻和馬修維納。）當前的代碼版本是基於 4.5-29從來源 randomForest包。(This is a Matlab (and Standalone application) port for the excellent machine learning algorithm `Random Forests - By Leo Breiman et al. from the R-source by Andy Liaw et al. http://cran.r-project.org/web/packages/randomForest/index.html ( Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener.) Current code version is based on 4.5-29 from source of randomForest package.)

用MATLAB实现频域平滑滤波以及图像去噪代码，可以实现数字图像处理及去噪(Smoothing filter frequency domain using MATLAB and image denoising code can achieve the digital image processing and denoising)

雅克比迭代求解线性方程组课设,BP神经网络用于函数拟合与模式识别，应用小区域方差对比，程序简单。( Jacobi iteration for solving linear equations class-based, BP neural network function fitting and pattern recognition, Application of small area variance comparison, simple procedures.)

外文资料里面的源代码，插值与拟合的matlab实现，采用波束成形技术的BER计算。( Foreign materials inside the source code, Interpolation and fitting matlab implementation, By applying the beam forming technology of BE.)

This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL