HH

LMS最小均方误差算法matlab仿真程序(LMS least mean square algorithm matlab simulation program)

说明：  这些源程序是最优化里的一些优化方法，用于解决简单函数，和多维函数的问题！(wegstein hair, is to optimize the course of a demand extreme value method for a simple function, find solutions and high precision!)

一种基于区域增长的图像分割方法，代码实现比较简单。(An image segmentation method based on regional growth, the code is relatively simple.)

根据导航文件数据对GPS伪距求解以及卫星位置计算(According to the file data on the GPS navigation solution and the pseudo-range calculation of satellite position)

模拟光ofdm中的minn算法 可以出图 源码 详细过程 以及注释 和必要的文字说明(the simulation of the minn in ofdm ， it can give off pictures and the descreption of the minn)

基于MATLAB的电力系统潮流计算程序设计的4节点极坐标牛顿-拉夫逊法潮流计算程序(MATLAB-based power flow calculation program designed 4-node polar coordinates Newton- Raphson power flow calculation program)

full bridge tamam pol and power electric

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

ofdm and its use and how to simulink it in matlab

采用matlab语言编写，相变沸腾的LBM模拟。(Using the matlab language to write, phase transition boiling LBM simulations)