Matlab fitting method to optimize the SNR in the frequency response curve to identify high error frequencies
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[stmfile,stmpath]=uigetfile('*mat','pick the mat file');
File = fullfile(char(stmpath),char(stmfile));
load(File);
[~,fileName,~] = fileparts(char(File)); % e.g., file is 'dp600_2_layers_L50.xlsx'
semilogx(No_smooth_x,'r-');hold on
grid on
grid minor
xlabel('Frequency(Hz)','FontSize',20)
set(gca,'FontSize',20);
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Mathieu NOE
2023-1-11
hello
this will reduce your plot noise but maybe you should improve the measurement method first ?
load('Noise.mat');
smooth_x = smoothdata(No_smooth_x,'gaussian',500);
% keep original data below f = 500 Hz
smooth_x(1:500) = No_smooth_x(1:500);
semilogx(No_smooth_x,'r-');hold on
semilogx(smooth_x,'b-');hold on
grid on
grid minor
xlabel('Frequency(Hz)','FontSize',20)
set(gca,'FontSize',20);
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