viterbi_deCODE

说明：  自己根据<最优化理论与基础>课本编的matlab程序 黄金分割法 自助输入目标函数及其梯度(Optimization: Gold Section Method Type in objective function and its gradient.)

以NACA0012 翼型为研究对象，采用拉格朗日法分析了重力对水滴撞击特性的影响，获得了过冷大水滴(SLD)撞击特性。(The influence of gravity on the droplet impingement property were analyzed with the Lagrangian method, and the supercooled large droplet (SLD) impingement property has been gotten based on the research of NACA0012 airfoil)

MIMO和OFDM在matlab上的仿真，本程序是毕业优秀论文仿真，很实用。(MIMO and OFDM on the matlab simulation, this program is excellent graduation thesis simulation, it is practical.)

matlab中文help 比较小，但对初学者比较有用。(matlab Chinese help relatively small, but more useful for beginners.)

说明：  基于matlab的衍射模拟，在毕业设计的时候顺便参考做的，有问题的话欢迎指出(Matlab simulation based on the diffraction, when the way in the graduate design reference do have problems, then welcome to point out)

一个教你如何用matlab写mimo系统的程序，可以任意改变编码方式和天线数目，(One teaches you how to write matlab mimo system program, you can change the encoding and the arbitrary number of antennas,)

用Matlab进行弹道解算的主程序。适合初学者使用。(Trajectory Calculation using Matlab main program. Suitable for beginners to use.)

基于谱熵法的语音信号端点检测方法的matlab程序，可以用于语音信号的处理(Endpoint detection method based on speech signal spectrum entropy method matlab program that can be used to handle voice signals)

principal_neumann (nom_maillage) a routine for implementing the EF P1 Lagrange for the Laplace equation following, with conditions Neumann on the mesh nom_maillage.msh

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)