obj_pro

这是我自己花了很多时间写的一个模式识别源码。奉献出来与感兴趣的朋友分享，绝对可靠。.. ( Dedication out with friends interested in sharing, absolutely reliable. ..)

本章对该文档的目的、功能范围、术语、相关文档、参考资料、版本更新进行说明。(The purpose of this chapter to the document, functional scope, terms, related documentation, reference materials, updated version will be described.)

Spectrum estimation using periodogram smoothing

说明：  空间直角坐标转换，BURSA模型解算七参数(Transformation of space rectangular coordinate and solution of seven parameters with bursa model)

MACH Kernel Implementation

PSO和GA的结合，优化结果明显提升，PSO是粒子群优化算法，GA是遗传算法(The combination of PSO and GA improves the optimization results. PSO is a particle swarm optimization algorithm and GA is a genetic algorithm.)

非常好的SIMULINK建模与仿真教程，有助于学习Simulink动态仿真！(Very good SIMULINK modeling and simulation tutorial, Simulink dynamic simulation help to learn!)

a practical malware analysis book

说明：  文章对OFDM技术作了介绍，主要涉及OFDM技术的基本原理，信道估计，同步技术等。(Articles on OFDM technology are introduced, mainly related to the basic principle of OFDM, channel estimation, synchronization technology.)

提出了一种求解电磁场有限元 边界元混合法所生成的线性方程组的有效方法 ———内观 法结合多波前法.由于该线性方程组的系数是一个部分稀疏部分满填充的矩阵,为了加速求解,应用内观法将系数矩阵分为 2块,一块是有限元法形成的稀疏矩阵,另一块是边界元法生成的满阵,然后用多波前法求解稀疏矩阵方程,用高斯 约当消去法解满阵方程. 采用该方法,计算了二维多层介质柱体的雷达散射截面.计算结果表明,该方法的计算效率远远高于传统的高斯法.(Proposed for solving mixed finite element boundary element linear equations generated by an effective method of Vipassana--- a combination of multi wave front method. Since the coefficients of linear equations is a part of the sparsely populated part of the full matrix, in order to speed up the solution, application of Vipassana coefficient matrix is ​ ​ divided into two, one is the finite element method for the formation of the sparse matrix, the other is the boundary element method generates the full array, and then use the multifrontal method for solving sparse matrix equation Gauss Jordan elimination method with full matrix equation solution. use this method to calculate the two-dimensional multi-layer dielectric cylinder of the radar cross section. The results show the computational efficiency of this method is much higher than the traditional Gaussian law.)