cfar

RBF（径向基神经网络）网络是一种重要的神经网络，RBF网络的训练分为两步，第一步是通过聚类算法得到初始的权值，第二步是根据训练数据训练网络的权值(RBF (radial basis function neural network) network is an important neural network, RBF network training is divided into two steps, first step is to get through the initial clustering algorithm weight, the second step is the training of the network based on training data weight)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

极大似然估计定位的编程实现，误差分析，节点数仿真等，比较全面，适合初学者(Maximum Likelihood Estimation targeted programming, error analysis, simulation, and other nodes, a more comprehensive, suitable for beginners)

《matlab6.5辅助例程和应用小波分析》一书的源码。版本老了点，但实例还很有用。(" Matlab6.5 auxiliary routines and application of wavelet analysis," the source book. Old version, but still very useful examples.)

Kalman滤波在跟踪轨迹时的使用，得到更好的图像(The use of Kalman filter in tracking trajectory, get a better image)

kd-tree 是一种常用的数据结构，它在搜索最近点中有普遍用处。该文件是一个用纯matlab写成的源代码。(kd-tree is a commonly used data structure, it is commonly used in searches for the nearest point. The file is a pure source code written in matlab.)

CGUI在STM上的移植, PDF文件,下载查看(The transplantation of CGUI on STM)

Mathematical formula

说明：  很有 用的LDPC译码程序，大家可以看看,很有借鉴作用(ldpc decoder)

单个光伏电池模型，非阵列，模块搭建工程实用模型(Single photovoltaic cell model, the non-array module to build practical engineering model)