How to remove noise from the noisy signal

Question

Rupa Sarkar 2019-7-18

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/472392-how-to-remove-noise-from-the-noisy-signal

回答： Vinai Datta Thatiparthi 2019-7-29

file2.xlsx

Hi, I am new to the MATLAB community. I have to remove noise from a signal. I followed a previous post and changed my signal to frequency. However, I don't know how to use ifft and filters properly. My excel spreadsheet is attached here. Any help will be grately appreciated. Thank you.

function [ output_args ] = Fourier4(  )
[D, S] = xlsread('file2.xlsx');
t = D(:,1);
EKG = D(:,2);
figure
plot(t, EKG)
L = numel(t);                                                       
tr = linspace(min(t), max(t), L);                                   
EKGr = resample(EKG, tr);   
Ts = mean(diff(t));
Fs = 1/Ts;                                                          
Fn = Fs/2;                                                         
MeanV = mean(EKGr);
FT_EKG = fft(EKGr-MeanV)/L;                                         
Fv = linspace(0, 1, fix(L/2)+1)*Fn;                               
Iv = 1:numel(Fv);                                                
figure
plot(tr, EKGr)
FT_EKGA = abs(FT_EKG(Iv));
figure
plot(Fv,FT_EKGA)
xlabel('Frequency (Hz)')
ylabel('Amplitude (mV)')
Y = ifft(FT_EKGA);
figure
Plot (tr, abs (Y))
  end
  

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Jan 2019-7-19

Before you can filter the noise, you have to define, what the noise is. Maybe you are interested in the low frequency signal, or in the high frequencies. We cannot guess, what "properly" means in your case.

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Answer 1

Vinai Datta Thatiparthi 2019-7-29

0
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在 MATLAB Online 中打开

Hi Rupa!

To begin with, I’d prefer using the command readtable instead of xlsread, since the former is the recommended command now. You can split the data accordingly using –

data = readtable('file2.xlsx');
t = table2array(data(:,1)); 
EKG = table2array(data(:,2));

Further, after you convert the signal into frequency domain using fft, MATLAB provides a wide range of functions as part of the Signal Processing Toolbox that can help you remove the noise. One of the easier functions to start with could be fir1 which allows you to design filters based on the different parameter details that you provide. You may use the function filter to apply the filter you created to the signal of your choice. Refer to this link for the necessary documentation –

https://www.mathworks.com/help/signal/ref/fir1.html

As an addition, consider using the Filter Designer App in MATLAB. The documentation is at –

https://www.mathworks.com/help/signal/examples/introduction-to-filter-designer.html

This detailed article contains multiple examples of filtering signals –

https://www.mathworks.com/help/signal/ug/filtering-data-with-signal-processing-toolbox.html