High and low frequencies are dependent on the application. A low frequency for wifi would be 2.4GHz, while a high frequency would be 5GHz. For human speech a low frequency is 300Hz, while a high frequency is 3000Hz. A graph of a fft (Fast Fourier Transform) allows us to visualize different frequencies. This example is adapted from [Matlab's fft help][1]. The following figure shows the first 100 out of $2^{20}$ samples of a time signal with two frequencies. Note how it is difficult to see the 1Hz component in this figure. ![Time signal][2] To see the frequency content we plot the spectrum as show in the following figure. Here we can clearly see the two frequencies - one at 1Hz and the other at 50Hz. ![Spectrum][3] Here is the code I used to generate these plots. <!-- language: matlab --> fs = 2^10; %sample frequency in Hz T = 1/fs; %sample period in s L = 2^20; %signal length t = (0:L-1) * T; %time vector A1 = 0.2; %amplitude of x1 (first signal) A2 = 1.0; %amplitude of x2 (second signal) f1 = 1; %frequency of x1 f2 = 50; %frequency of x2 x1 = A1*sin(2*pi*f1 * t); %sinusoid 1 x2 = A2*sin(2*pi*f2 * t); %sinusoid 2 y = x1 + x2; %Plot signal figure; set(gcf,'Color','w'); %Make the figure background white plot(fs*t(1:100), y(1:100)); set(gca,'Box','off'); %Axes on left and bottom only str = sprintf('Signal with %dHz and %dHz components',f1,f2); title(str); xlabel('time (milliseconds)'); ylabel('Amplitude'); %Calculate spectrum Y = fft(y)/L; ampY = 2*abs(Y(1:L/2+1)); f = fs/2*linspace(0,1,L/2+1); i = L/fs * (max(f1,f2)) + 1; %show only part of the spectrum %Plot spectrum. figure; set(gcf,'Color','w'); %Make the figure background white plot(f(1:i), ampY(1:i)); set(gca,'Box','off'); %Axes on left and bottom only title('Single-Sided Amplitude Spectrum of y(t)'); xlabel('Frequency (Hz)'); ylabel('|Y(f)|'); [1]: http://www.mathworks.com/help/techdoc/ref/fft.html [2]: https://i.sstatic.net/0MIIu.png [3]: https://i.sstatic.net/kAqQ3.png