Minutiae

通过位移,速度这六个量来求得飞行器轨道的六个基本要素(Through displacement, velocity, volume of these six aircraft to strike the six basic elements of the track)

功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。(Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe)

说明：  利用锁相环，比较好的实现了载波同步。。。(PLL)

This is Understanding LTE with Matlab book Houma Zarrinkoub

用matlab对M=8的PSK系统进行蒙特卡罗仿真，分析其误码率(Using matlab for M = 8 the PSK system Monte Carlo simulation, to analyze the bit error rate)

根据cpso算法给出的一个matlab代码，全，添加测试函数即可运行(According cpso given an algorithm matlab code, full, add test functions to run)

固定范围内采用GPSR路由协议的最佳路径选择matlab程序(Within a fixed range using the best path routing protocol GPSR choice matlab program)

本人亲手搭建的三相异步电机仿真，内容包括电机堵转、启动、调速，同时包含word说明。本资料全经过实验仿真确定无误，与网上花里胡哨的资源不一样！(I built the three-phase asynchronous motor simulation, including the motor plugging, starting, speed regulation, and including the word description, the data all through the experiment simulation.)

磁滞曲线的建立，基于MATLAB编辑器条件下，运用数学公式解方程的方法，求解微分方程(Establishment of hysteresis curve)

project, which shows the biomed-signal processing. Very simple