heat

Greedy Group Sparsity Promoting Optmization

这个源码是MIMO中的预编码技术的概括，包含了大部分有关MIMO的代码，能够帮助大家(The source is a MIMO pre-coding technology in general, including most of the code relating to MIMO, can help you)

在自动控制系统的过程中，白噪声的产生方法，MIT 稳定方程 持续时间 稳定时间(The automatic control system of the process, the white noise generation method, MIT stabilization stabilization time duration equation)

用matlab编程实现车牌字符的识别，在识别中运用了模板匹配的方法(Matlab programming realize license plate character recognition, the recognition using a template matching method )

对256×256大小的8bit灰度lena图像进行仿真计算，稀疏矩阵采用DCT矩阵，观测矩阵采用高斯随机矩阵，重构算法采用OMP（正交匹配追踪）算法。 (256256 size 8bit grayscale lena image simulation, sparse matrix DCT matrix, and observation matrix using Gaussian random matrix reconstruction algorithm using OMP (orthogonal matching pursuit) algorithm.)

时域自适应滤波中基于后验概率的格型RLS算法(奀郖赻巠crown thinning recommended price笢Guang Ya Carex quilt is made up of trace倰cavity RLS呾Yang)

This program simulates an Fuzzy Model Reference Learning Control for a tanker ship.

Simulation of ESPRIT

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

我写的改进中心点的混合高斯分布的EM算法(I wrote to improve the center of the EM algorithm for Gaussian mixture)