75 lines
2.0 KiB
Mathematica
75 lines
2.0 KiB
Mathematica
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% Matlab Init :noexport:ignore:
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clear; close all; clc;
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%% Intialize Laplace variable
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s = zpk('s');
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%% Initialize ans with org-babel
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ans = 0;
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% Load data
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amp_off = load('mat/data_003.mat', 'data'); amp_off = amp_off.data(:, [1,3]);
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amp_20d = load('mat/data_004.mat', 'data'); amp_20d = amp_20d.data(:, [1,3]);
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amp_40d = load('mat/data_005.mat', 'data'); amp_40d = amp_40d.data(:, [1,3]);
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amp_60d = load('mat/data_006.mat', 'data'); amp_60d = amp_60d.data(:, [1,3]);
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% Time Domain
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% The time domain signals are shown on figure [[fig:ampli_noise_time]].
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figure;
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hold on;
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plot(amp_off(:, 2), amp_off(:, 1), 'DisplayName', 'OFF');
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plot(amp_20d(:, 2), amp_20d(:, 1), 'DisplayName', '20dB');
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plot(amp_40d(:, 2), amp_40d(:, 1), 'DisplayName', '40dB');
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plot(amp_60d(:, 2), amp_60d(:, 1), 'DisplayName', '60dB');
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hold off;
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legend('Location', 'northeast');
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xlabel('Time [s]');
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ylabel('Voltage [V]');
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% Frequency Domain
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% We first compute some parameters that will be used for the PSD computation.
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dt = amp_off(2, 2)-amp_off(1, 2);
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Fs = 1/dt; % [Hz]
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win = hanning(ceil(10*Fs));
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% Then we compute the Power Spectral Density using =pwelch= function.
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[pxoff, f] = pwelch(amp_off(:,1), win, [], [], Fs);
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[px20d, ~] = pwelch(amp_20d(:,1), win, [], [], Fs);
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[px40d, ~] = pwelch(amp_40d(:,1), win, [], [], Fs);
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[px60d, ~] = pwelch(amp_60d(:,1), win, [], [], Fs);
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% We compute the theoretical ADC noise.
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q = 20/2^16; % quantization
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Sq = q^2/12/1000; % PSD of the ADC noise
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% Finally, the ASD is shown on figure [[fig:ampli_noise_psd]].
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figure;
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hold on;
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plot(f, sqrt(pxoff), 'DisplayName', 'OFF');
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plot(f, sqrt(px20d), 'DisplayName', '20dB');
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plot(f, sqrt(px40d), 'DisplayName', '40dB');
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plot(f, sqrt(px60d), 'DisplayName', '60dB');
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plot([0.1, 500], [sqrt(Sq), sqrt(Sq)], 'k--');
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hold off;
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set(gca, 'xscale', 'log');
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set(gca, 'yscale', 'log');
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xlabel('Frequency [Hz]'); ylabel('ASD of the measured Voltage $\left[\frac{V}{\sqrt{Hz}}\right]$')
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legend('Location', 'northeast');
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xlim([0.1, 500]);
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