DFT_OFDM

对于学习信号处理的同学们，需要数值分析的一些知识，如拟合、松弛迭代等等都是有用的数值分析方法(For students studying signal processing, numerical analysis requires some knowledge of relaxation that a useful method for numerical analysis)

说明：  经典功率谱估计的matlab仿真。利用的是直接法(classic power spectrum estimation of Matlab simulation. The use of the direct method)

学会用MATLAB编写程序； 学会一维搜索法； 精确的一维线性搜索法：0.618法； 非精确的一维线性搜索法：goldstein法；(Learn how to use MATLAB programming Society of one-dimensional search method precise linear one-dimensional search method: 0.618 law non-accurate one-dimensional linear search method: goldstein law )

中国移动多媒体广播(CMMB)发射端的MATLAB实现(China Mobile Multimedia Broadcasting (CMMB) transmitter of the MATLAB implementation)

A small GUI for displaying Newton-Raphson fractals (i.e. the basins of attraction) of complex polynomials. See for example http://en.wikipedia.org/wiki/Newton_fractal.

采用Hopfield网络解决旅行商问题，收敛速度快。(using Hopfield network to solve the traveling salesman problem, and fast convergence.)

双闭环直流脉宽调速系统仿真，采用外环为转速环，内环为电流环(Double Loop DC PWM System Simulation)

如果G的边集E(G)中有个子集M，满足M中的任何两条边 都不邻接，则M就是图G的一个匹配。包含边数最多的匹配 称为最大匹配，最大匹配所包含的边数称为最大匹配数。当 G是二分图时，问题就比较特殊了，这就是我们要解决 的问题——最大二分匹配。(If there is a subset M in the edge set E (G) of G, if any two edges in M are not adjacent, then M is a match of graph G. The match with the largest number of edges is called the maximum matching, and the number of edges contained in the maximum matching is called the maximum matching number. When G is a two point graph, the problem is very special. This is the problem we want to solve -- the biggest two points matching.)

雷达成像技术包含（一）线性调频信号的匹配及源代码；（二）雷达采集信号的距离向压缩及源代码（三）雷达采集信号的距离徙动校正与方位向压缩及源代码(The radar imaging technique include (a) linear FM signal matching and source code (b) the distance of the radar signal acquisition to the radar signal acquisition, compression and source code (c) distance migration correction and azimuth compression and source code)

本自适应LSL算法实现线性预测 以及考察LSL算法的收敛性： 与LMS、RLS算法进行性能比较 (The LSL algorithm adaptive linear prediction and to study the LSL algorithm convergence: the LMS, RLS algorithm performance comparison)