同步提取变换matlab代码-优快云博客

本文链接：https://blog.youkuaiyun.com/matlab_dingdang/article/details/136423362

本文提出了一种新的时间-频率分析方法，利用同步抽样变换和迭代重分配策略，以解决强时变信号的模糊TF表示问题，提高信号重构能力，适用于实时应用。实验结果显示，新方法在处理强时变和噪声信号时表现出更好的性能。

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✅作者简介：热爱科研的Matlab仿真开发者，修心和技术同步精进，代码获取、论文复现及科研仿真合作可私信。

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🔥 内容介绍

Time-frequency (TF) analysis (TFA) method is an important tool in industrial engineering fields. However, restricted to Heisenberg uncertainty principle or unexpected cross terms, the classical TFA methods often generate blurry TF representation, which heavily hinder its engineering applications. How to generate the concentrated TF representation for a strongly time-varying signal is a challenging task. In this paper, we propose a new TFA method to study the nonstationary features of strongly time-varying signals. The proposed method is based on synchrosqueezing transform and employs an iterative reassignment procedure to concentrate the blurry TF energy in a stepwise manner, meanwhile retaining the signal reconstruction ability. Two implementations of the discrete algorithm are provided, which show that the proposed method has limited computational burden and has potential in real-time application. Moreover, we introduce an effective algorithm to detect the instantaneous frequency trajectory, which can be used to decompose monocomponent modes. Numerical and real-world signals are employed to validate the effectiveness of the proposed method by comparing with some advanced methods. By comparisons, it is shown that the proposed method has the better performance in addressing strongly time-varying signals and noisy signals.

📣 部分代码

%Figures 18-23clear;load('batdata2.mat');SampFreq = 1000000/7;n=length(data);time=(1:n)/SampFreq;fre=(SampFreq/2)/(n/2):(SampFreq/2)/(n/2):(SampFreq/2);time=time*1000;fre=fre/1000;x1=0.00105; x2=0.001673;y1=31790;   y2=49640;x1=x1*1000;x2=x2*1000;y1=y1/1000;y2=y2/1000;p1 =  -1.69e+011 ;p2 =  4.045e+009  ;p3 = -2.715e+007  ;p4 =  7.072e+004  ;x=time/1000;I = p1*x.^3 + p2*x.^2 + p3*x + p4;p=INT(I,x);c1=3*p1*x.^2 + 2*p2*x + p3;c2=6*p1*x + 2*p2;c3=6*p1*ones(1,400);c4=zeros(1,400);[Tr] = RS_Y(data,45);[Ts] = SST_Y(data,45);Ptfr = PTFA(data,150,SampFreq,c1,c2,c3,c4);Dtfr = DTFA(data,150,SampFreq,I,p);[SEO Te tfr] = SET_Y(detrend(data),45);[Cs1, Es1] = brevridge_mult(abs(Te), 1:400, 4, 1, 5);[Cs2, Es2] = brevridge_mult(abs(Ts), 1:400, 4, 1, 5);[Cs3, Es3] = brevridge_mult(abs(Tr), 1:400, 4, 1, 5);[Cs4, Es4] = brevridge_mult(abs(Dtfr), 1:400, 4, 1, 5);%.......................Fig. 18....................figuresuptitle('Fig. 18');subplot(121)plot(time,data);xlabel('Time / ms');ylabel('Amplitude');axis([0 time(end) -0.25 0.15]);ft=abs(fft(data))/200;subplot(122)plot(fre,ft(1:end/2));xlabel('Fre / kHz');ylabel('Amplitude');axis([0 fre(end) 0 0.018]);%....................Fig. 19.........................figuresuptitle('Fig. 19');ha=subplot(221);imagesc(time,fre,abs(tfr));xlabel('Time / ms');ylabel('Fre / kHz');axis xycolormap jet;ha=subplot(222);imagesc(time,fre,abs(SEO));xlabel('Time / ms');ylabel('Fre / kHz');axis xycolormap(gca, 1-hot(256));ha=subplot(223);imagesc(time,fre,abs(Te));xlabel('Time / ms');ylabel('Fre / kHz');axis xyrectangle('Position',[x1 y1 x2-x1 y2-y1],'EdgeColor','red','Linewidth',1);colormap jet;ha=subplot(224);imagesc(time,fre,abs(Te));xlabel('Time / ms');ylabel('Fre / kHz');axis xyset(ha,'xlim',[x1 x2],'ylim',[y1 y2]);colormap jet;%......................Fig. 20....................figuresuptitle('Fig. 20');ha=subplot(221);imagesc(time,fre,abs(Ts));xlabel('Time / ms');ylabel('Fre / kHz');axis xyrectangle('Position',[x1 y1 x2-x1 y2-y1],'EdgeColor','red','Linewidth',1);colormap jet;ha=subplot(222);imagesc(time,fre,abs(Ts));xlabel('Time / ms');ylabel('Fre / kHz');axis xyset(ha,'xlim',[x1 x2],'ylim',[y1 y2]);colormap jet;ha=subplot(223);imagesc(time,fre,abs(Tr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyrectangle('Position',[x1 y1 x2-x1 y2-y1],'EdgeColor','red','Linewidth',1);colormap jet;ha=subplot(224);imagesc(time,fre,abs(Tr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyset(ha,'xlim',[x1 x2],'ylim',[y1 y2]);colormap jet;%.......................Fig. 21........................figuresuptitle('Fig. 21');ha=subplot(221);imagesc(time,fre,abs(Ptfr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyrectangle('Position',[x1 y1 x2-x1 y2-y1],'EdgeColor','red','Linewidth',1);colormap jet;ha=subplot(222);imagesc(time,fre,abs(Ptfr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyset(ha,'xlim',[x1 x2],'ylim',[y1 y2]);colormap jet;ha=subplot(223);imagesc(time,fre,abs(Dtfr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyrectangle('Position',[x1 y1 x2-x1 y2-y1],'EdgeColor','red','Linewidth',1);colormap jet;ha=subplot(224);imagesc(time,fre,abs(Dtfr));xlabel('Time / ms');ylabel('Fre / kHz');axis xyset(ha,'xlim',[x1 x2],'ylim',[y1 y2]);colormap jet;%....................Fig. 22........................c=200/fre(end);figuresuptitle('Fig. 22');subplot(221)plot(time,Cs1/c,'b-');xlabel('Time / ms');ylabel('Fre / kHz');axis([0 time(end) 0 fre(end)]);subplot(222)plot(time,Cs2/c,'b-');xlabel('Time / ms');ylabel('Fre / kHz');axis([0 time(end) 0 fre(end)]);subplot(223)plot(time,Cs3/c,'b-');xlabel('Time / ms');ylabel('Fre / kHz');axis([0 time(end) 0 fre(end)]);subplot(224)plot(time,Cs4/c,'b-');xlabel('Time / ms');ylabel('Fre / kHz');axis([0 time(end) 0 fre(end)]);%.....................Fig. 23.......................for k=1:4for j=1:400Te_sig(k,j)=real(Te(Cs1(k,j),j));endendTe_sig(4,1:200)=0;rSig=sum(Te_sig);figuresuptitle('Fig. 23');subplot(321);plot(time,Te_sig(1,:));axis([0 2.8 -0.11 0.11]);subplot(322);plot(time,Te_sig(2,:));axis([0 2.8 -0.13 0.13]);subplot(323);plot(time,Te_sig(3,:));axis([0 2.8 -0.05 0.05]);subplot(324);plot(time,Te_sig(4,:));axis([0 2.8 -0.03 0.03]);subplot(325);plot(time,data,'color','k');hold on;plot(time,sum(Te_sig),'r--');axis([0 2.8 -0.22 0.15]);subplot(326);plot(time,sum(Te_sig)-data','r--');axis([0 2.8 -0.22 0.15]);