Isolating a single pulse by removing noise

I hope my title wasn't misleading, I simply want to remove the oscillatory noise from the pulse I obtain from a monostable multivibrator.

I have attached a picture of the Time Domain waveform (which is the same as the snapshot from the o-scope) below, I want to isolate the 50ns initial pulse. I am thinking of using a low-pass filter to achieve that but inorder to do so I need to find the frequencies of the noise.

I converted the time domain waveform using FFT Spectral Analysis https://www.mathworks.com/help/matlab/math/fft-for-spectral-analysis.html;jsessionid=bc43693596ebb77a7d9866ab030f

And I have attached the plots for the Frequency Domain graphs that I obtained after using FFT.

zoomed into the range of 0~20 Hz

I am having a hard time identifying which frequencies are from the noise and which frequency is that of the 50ns initial pulse that I am interested in, so I can find the ideal resistor-capacitor combination for the low pass filter to isolate the pulse from the noise

Any help would be greatly appreciated. I have attached the CSV file I obtained from the o-scope and my code incase that helps.

Thanks in advance!

clc; clear all; close all
A = dlmread("F0000CH1.CSV",",",0,3);
Time = 1e9.*A(:,1);
Voltage = A(:,2);
figure
plot(Time,Voltage,'LineWidth',2)
title('Time Domain Function')
ylabel('Voltage (V)')
xlabel('Time (ns)')
xlim([-125 400])
ylim([-4.5 6])

%frequency domain
S=numel(Time);
FFT = fft(Voltage,S);
Pyy = FFT.*conj(Voltage)/S;
f = (1000/S)*(0:floor(S/2));
figure
plot(f,Pyy(1:floor(S/2)+1))
title('Frequency Domain')
xlabel('Frequency (Hz)')
ylabel('dB/frequency')
figure
plot(f(1:50),Pyy(1:50),'LineWidth',2)
title('Frequency Domain')
xlabel('Frequency (Hz)')
ylabel('dB/frequency')

Answer 1

[Star Strider]

Try this:

A = dlmread('F0000CH1.csv',",",0,3);
Time = 1e9.*A(:,1);
Voltage = A(:,2);

figure
plot(Time,Voltage,'LineWidth',2)
title('Time Domain Function')
ylabel('Voltage (V)')
xlabel('Time (ns)')
xlim([-125 400])
ylim([-4.5 6])

L = numel(Time);                                            % Signal Length
Ts = mean(diff(Time));                                      % Sampling Interval
Fs = 1/Ts;                                                  % Sampling Frequency
Fn = Fs/2;                                                  % Nyquist Frequency
FT_V = fft(Voltage)/L;                                      % Normalised Fourier Transform
Fv = linspace(0, 1, fix(L/2)+1)*Fn;                         % Frequency Vector
Iv = 1:numel(Fv);                                           % Index Vector

figure
plot(Fv, abs(FT_V(Iv))*2)
grid
xlim([0  0.5])

Wp = 0.045;                                                 % Passband Frequency (Normalised)
Ws = 0.050;                                                 % Stopband Frequency (Normalised)
Rp =  1;                                                    % Passband Ripple
Rs = 50;                                                    % Passband Ripple (Attenuation)
[n,Wp] = ellipord(Wp,Ws,Rp,Rs);                             % Elliptic Order Calculation
[z,p,k] = ellip(n,Rp,Rs,Wp);                                % Elliptic Filter Design: Zero-Pole-Gain 
[sos,g] = zp2sos(z,p,k);                                    % Second-Order Section For Stability

figure
freqz(sos, 2^16, Fs)                                        % Filter Bode Plot

Voltage_filt = filtfilt(sos, g, Voltage);                   % Filter Signal

figure
plot(Time,Voltage_filt,'LineWidth',2)
title('Time Domain Function')
ylabel('Voltage (V)')
xlabel('Time (ns)')
xlim([-125 400])
ylim([-4.5 6])

I chose a passband frequency of 0.045 Hz and a stopband frequency of 0.050 Hz, based on the Fourier transform results, since it appeared to give good results. This code designs an 7-order elliptic filter, since these filters are efficient. Experiment with the filter characteristics to decide on the paramerers for your hardware filter.

[Hans123]

wow, this is on another level! I am a newcomer to this topic and I thought I could use a simple DIY resistor-capacitor combination to remove the noise but this is complicated than that.

I am working with nanosecond pulses I should take into accound the rise and fall times of all the components that I am including in my set-up, so I am trying to find the most feasible method to tackle this issue.

As always, thank you Star Strider! I did not expect to see a Bode plot, but you always come through. Thanks again for blessing this forum!

[Star Strider]

As always, my pleasure!

I very much appreciate your compliments!