threephasePWMinverterusinguniversalbridge

说明：  这是一个完善的RVM算法。其性能良好，代码清晰。能够很好的用于分类。(This is a perfect RVM algorithm. Its good performance, the code clear. Can be good for classification.)

Clark变换与Inv_Clark变换，引入输入信号进过测试能够实现功能(Clark and Inv_Clark)

利用firpmord和firpm函数设计双带通滤波器，其指标为，第一带通指标：f =4kHz,f =5 kHz ,f =3.6 kHz ,f =5.4 kHz 第二带通指标：f =6kHz,f =7 kHz ,f =5.6 kHz ,f =7.4 kHz 通带衰耗A <3dB，阻带衰耗A >40dB，抽样频率f =20kHz。(Double belt pass filter using firpmord and firpm function design, for its indicators, through the first area index: f = 4 kHz, f = 5 kHz, f = 3.6 kHz, f = 5.4 kHz The second bandpass indicators: f = 6 kHz, f = 7 kHz, f = 5.6 kHz, f = 7.4 kHz Pass band attenuation A < 3 db, stop-band attenuation A > 40 db, f = 20 KHZ sampling frequency.)

for all design of CDMA optique and its solutions

降维状态观测器是非常重要的一类观测器，它使用状态反馈构成闭环系统的物理实现成为可能。降维状态观测器的设计方法很多，这里提出主要的两种：(Reduced-order state observer is a very important class of observer, which uses state feedback closed loop system, the physical realization possible. Reduced-order state observer design method are many, here for the main two:)

分析psk调制与解调的函数，并有误码率分析(psk)

emd 分解程序 希尔伯特换变换的程序有图(emd decomposition process Hilbert transform procedures change map)

在计算机上产生一组实验数据，首先产生一段零均值白噪声数据u（n）,令功率为 ，让u(n)通过一个三阶FIR： 得到y(n). .y(n)上加三个实正弦信号f1’=0.1,f2’=0.25,f3’=0.26调整 和正弦信号幅度信噪比大致为10dB,50dB,50dB. (1) 令N=256,描绘xn波形； (2)得出真实功率谱密度 . (3) 利用此实验数据Pisarenko谐波分解法估计该实验数据的正弦频率及幅度。 (On the computer to generate a set of experimental data, first generate a zero mean white noise data u (n), so that power, let u (n) through a third-order FIR: get y (n).. Y (n) added three real sinusoidal signal f1 ' = 0.1, f2' = 0.25, f3 ' = 0.26 and sine signal amplitude adjustment signal to noise ratio is approximately 10dB, 50dB, 50dB. (1) that N = 256, depicted xn waveform (2) the true power spectral density obtained. (3) using this experimental data, Pisarenko harmonic decomposition method to estimate the experimental data of the sinusoidal frequency and amplitude.)

shape context的MATLAB一个Demo，好像是从原作者网站上下下来的(shape context of MATLAB a Demo, seems to be down from the original author site down)

it s really good i mean very very good what I meant is it s really good