Hi Fima,
Yes, MATLAB has several tools and functions that can help you generate a signal, add high-frequency noise, and take samples for DSP (Digital Signal Processing) applications. Below is an example of how you can generate a 10 kHz cosine wave, add high-frequency noise to it, and then take samples from it. You can adjust the parameters and the downsample factor as needed for your specific application.
% Parameters
Fs = 100e3; % Sampling frequency (100 kHz)
duration = 0.01; % Duration of the signal (10 ms)
t = 0:1/Fs:duration-1/Fs; % Time vector of 10 ms
f = 10e3; % Frequency of the cosine wave (10 kHz)
f_noise = 50e3; % Frequency of the noise (50 kHz)
noise_amplitude = 1; % Amplitude of the noise
% Generate the 10 kHz cosine wave
signal = cos(2*pi*f*t);
% Generate high-frequency noise
noise = noise_amplitude * cos(2*pi*f_noise*t);
% Add noise to the signal
noisy_signal = signal + noise;
% Plot the signals
figure;
subplot(3,1,1);
plot(t, signal);
title('Original 10 kHz Cosine Wave');
xlabel('Time (s)');
ylabel('Amplitude');
subplot(3,1,2);
plot(t, noise);
title('High-Frequency Noise (50 kHz)');
xlabel('Time (s)');
ylabel('Amplitude');
subplot(3,1,3);
plot(t, noisy_signal);
title('Noisy Signal');
xlabel('Time (s)');
ylabel('Amplitude');
% Downsample the signal using resample (e.g., by a factor of 10)
downsample_factor = 10;
downsampled_signal = resample(noisy_signal, 1, downsample_factor);
downsampled_time = linspace(0, duration, length(downsampled_signal));
% Plot the downsampled signal
figure;
plot(downsampled_time, downsampled_signal, '-o');
title('Downsampled Noisy Signal');
xlabel('Time (s)');
ylabel('Amplitude');
% Save downsampled signal to a variable (e.g., for later use in FIR filtering)
testData = downsampled_signal;
% Display the first few samples
disp('First few samples of the downsampled noisy signal:');
disp(testData(1:10));
