EX5

一个鲁榜自适应Capon波束形成器(Robust Capon Beamforming)的实现算法。该算法是先进的，广泛使用在信号处理和通信领域的有效波束形成算法。(a list Capon adaptive beamforming (Robust Capon Beamforming) algorithm. The algorithm is an advanced, widely used in signal processing and communications, the effective beam forming algorithms.)

说明：  温克、孙克华，清华大学出版社。神经网络算法、遗传算法、粒子群算法、免疫算法、蚁群算法等等。(Neural network algorithm, genetic algorithm, particle swarm algorithm, immune algorithm, ant colony algorithm, etc.)

this is to find the information of any image database

混合隶属度随机块模型，用于进行社区划分，检测重叠社区，节点分组等( Mixed-Membership Stochastic Block mold，which is a scalable approach to community detection that discovers overlapping communities in massive realworld networks.)

非常经典的最优化程序，里面黄金分割、拟牛顿、对偶单纯形，故向大家推荐(Very classical optimization procedures, which Golden Section, Quasi-Newton, dual simplex, so to recommend)

matlab中关于矩阵的分解，行列式，逆。矩阵的特征值，矩阵函数，奇异值分解，最小二乘法，函数的导数以及偏倒数，梯度，切平面以及积分与卷积等的原理，以及具体程序编写的例子(matlab on Matrices, determinant, inverse. Eigenvalues, matrix functions, singular value decomposition, least squares, and the partial derivative of the function inverse, gradient, tangent plane, and the principle of integration and convolution, etc., as well as specific examples of programming)

The radially averaged power spectrum (RAPS) is the direction-independent mean spectrum, i.e. the average of all possible directional power spectra. This function computes and plots the RAPS of an input image. The function was written to produce the RAPS for square weather radar reflectivity images so you will have to relabel the plot axes and title to suit your needs. The radially averaged power spectrum provides a convenient means to view and compare information contained in 2D spectra in 1D

该文件为matlab7.0的学校资料，希望对需要者能提供帮助(it is a process about matlab7.0)

说明：  LBG算法设计矢量量化码书的函数，需要给出训练序列x,矢量维数K和码书长度CN，返回根据训练序列给出的最小误差码书。(LBG algorithm for vector quantization codebook design function , you need to give training sequence x, vector dimension K and codebook length CN, return according to the minimum error given training sequence codebook . )

稀疏约束的非负矩阵分解Non-negative Matrix Factorization with Sparseness Constraints(Non-negative Matrix Factorization with Sparseness Constraints)