compute the spectrum of a signal with fft, round up the number of samples for the fft to the next power of 2. plot the spectrum in db scale for the amplitude in matlab

main.m
% generate a signal
fs = 1000; % sampling frequency 
t = 0:1/fs:1; % time vector
f = 25; % signal frequency
x = cos(2*pi*f*t) + randn(size(t)); % add some noise to the signal

% compute the spectrum
N = 2^nextpow2(length(x)); % round up to next power of 2
X = fft(x, N); % compute FFT
mag = abs(X).^2; % compute power spectrum

% plot the spectrum in dB scale
frequencies = linspace(0, fs/2, N/2+1);
dB = 10*log10(mag(1:N/2+1)); % convert to dB scale
plot(frequencies, dB);
xlabel('Frequency (Hz)');
ylabel('Magnitude (dB)');
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