GauPydDec

我们提出了一种新的方法来实现全光 微波使用光纤布拉格光栅阵列滤波 相同的反射率。确定了过滤器攻丝系数 通过一个宽带光源的光谱分布和 光栅的中心波长。由于光纤布拉格 光栅有相同的反射率，其特征 高均匀度的光栅是可能的，从而简化了 光纤布拉格光栅的制作，降低了实现 错误。此外，该宽带光的光谱分布 源可以控制使用的光学过滤器，可用于 控制滤波器系数的滤波器的旁瓣抑制。一个 微波滤波器采用四个光纤布拉格光栅的实验 实施。 (We propose a novel approach to realizing all-optical microwave filtering using an array of fiber Bragg gratings with identical reflectivities. The filter tapping coefficients are determined by the spectrum profile of a broadband light source and the central wavelengths of the gratings. Since the fiber Bragg gratings have identical reflectivities, the characteristics of the gratings with high uniformity are possible, which simplifies the fiber Bragg grating fabrication and reduces the implementation error. In addition, the spectrum profile of the broadband light source can be controlled using an optical filter, which could be used to control the filter coefficients to suppress the filter sidelobes. A microwave filter using four fiber Bragg gratings is experimentally implemented.)

这是一本信号与系统方向的圣经，我这里上传上来，希望对大家有用。(It is a bible in the aspect of signal and system. I upload it and want to share with people who need it and hope to help him/her.)

说明：  小波变换通过matlab实现s小波变换代码，给出变换结果。(Wavelet transform, through the realization of s wavelet transform matlab code, given the results of transformation.)

fft calaculation of dc-dc signal

ch3=softt(h3,thr1 clear clc I=imread( lena512.bmp ) imshow(I) I=double(I) II=I+30*randn(size(I)) figure imshow(II,[]) [a1,h1,v1,d1]=dwt2(II, sym8 ) [a2,h2,v2,d2]=dwt2(a1, sym8 ) [a3,h3,v3,d3]=dwt2(a2, sym8 ) sigma=median(abs(d1(:)))/0.6745 x=3*sigma thr1=x*2^(-1) thr2=x*2^(-0.5) thr3=x 小波图像去噪( ch3=softt(h3,thr1 clear clc I=imread( lena512.bmp ) imshow(I) I=double(I) II=I+30*randn(size(I)) figure imshow(II,[]) [a1,h1,v1,d1]=dwt2(II, sym8 ) [a2,h2,v2,d2]=dwt2(a1, sym8 ) [a3,h3,v3,d3]=dwt2(a2, sym8 ) sigma=median(abs(d1(:)))/0.6745 x=3*sigma thr1=x*2^(-1) thr2=x*2^(-0.5) thr3=x )

Sparsity-Promoting Optimal Wide-Area Control of Power Networks

Our project is to describe the Brownian Motion and Geometric Brownian Motion. This project is to simulate the price shock. Then we use Geometric Brownian motion to describe the movement of shocks’ price. The program is produced by Matlab.(Application of Ito’s Lemma to a Stock Price Process)

this is a simulink program tat simulates a an iduction motor being controlled via a converter and has a load that consists of an elevor load and a counterweight

kalman滤波在嵌入式中的应用，可用于智能车的制作，对陀螺仪和加速度计进行优化。(kalman filtering applications in embedded in can be used smart car production, gyroscopes and accelerometers for optimization.)

—Series capacitors (SCs) are installed on long transmission lines to reduce the inductive reactance