ofdm

Principal Components Analysis (PCA) is used to compress data in such a way that the least information is lost. It does so by truncating data and thereby leaving out the data which is of the least importance to the information stored in the data. This PCA process is called dimensionality reduction,

把matlab计算后的数据保存成obj格式的文件，能保存点和点点之间的连接关系，即obj格式的中的v和f(Obj format to save data into files that can save the points and little connection between the relationship that the v in obj format and f)

mimo-ofdm信道估计的不同算法比较,可以直接运行(mimo- ofdm channel estimation algorithms can be compared directly operation)

灰度梯度共生矩阵 H 归一化灰度梯度矩阵 H_basic 小梯度优势 T1 大梯度优势 T2 灰度分布的不均匀性 T3 梯度分布的不均匀性 T4 能量 T5 灰度平均 T6 梯度平均 T7 灰度均方差 T8 梯度均方差 T9 相关 T10 灰度熵 T11 梯度熵 T12 混合熵 T13 惯性 T14 逆差矩 T15(GGCM H normalized gray gradient matrix H_basic small advantage T1 gradient big advantage T2 gradient gray uneven distribution of T3 gradient uneven distribution of energy T5 gray T4 average T6 average gradient gray T7 average gradient T8 variance variance T9 were related to T10 T11 gradient gray entropy entropy of mixing entropy T12 T13 inertia moment T15 T14 deficit)

说明：  简要介绍了OFDM的发展状况及基本原理, 文章对OFDM 系统调制与解调技术进行了解析，得到了OFDM 符号的一般表达式，给出了OFDM 系统参数设计公式和加窗技术的原理及基于IFFT/FFT 实现的OFDM 系统模型，阐述了运用IDFT 和DFT 实现OFDM 系统的根源所在,重点研究了理想同步情况下,保护时隙(CP)、加循环前缀前后和不同的信道内插方法在高斯信道和多径瑞利衰落信道下对OFDM系统性能的影响。在给出OFDM系统模型的基础上,用MATLAB语言实现了传输系统中的计算机仿真并给出参考设计程序。最后给出在不同的信道条件下,研究保护时隙、循环前缀、信道采用LS估计方法对OFDM系统误码率影响的比较曲线,得出了较理想的结论。(Generation of OFDM Communication System)

这里是通信领域中各种基带信号（非常全，几乎最新的都有），用matlab编写，给出了相应的带宽和功率谱密度，很值得学习通信的看看(Here are the various communications baseband signal (very full, almost all the latest), written with matlab, the corresponding bandwidth and power spectral density, it is worth learning to see communication)

基于Simulink的模拟双边带与单边带调制系统设计(Simulink-based simulation of double sideband and single sideband modulation system design)

PID控制直流电机源码（simulink），可以直接运行。(PID control of DC source, can be directly run.)

离散系统的MATLAB实现。学习利用matlab求解系统频率响应的方法；学习利用matlab求解系统输出响应的方法； (MATLAB realization of discrete systems. Learning methods for solving systems using matlab frequency response learning methods for solving systems using matlab output response )

遗传算法从代表问题可能潜在的解集的一个种群开始的，而一个种群则由经过基因编码的一定数目的个体组成。本代码以旅行商问题为例，详细介绍遗传算法的使用方法。(A genetic algorithm the representation of the solution set of potentially the beginning, but after a certain number of the population the gene encoding the individual components. The code to the traveling salesman problem, for example, describes the use of genetic algorithms.)