patterns of variations that represent/encode information
expressed in terms of waves — sinusoidal, sawtooth, triangle, square
waves have period, amplitude, frequency, wavelength
a function of time and volume (amplitude) — time t => s(t)
continuous if there is a volume for each point in time
speech is one-dimensional — only changes in time
an image is two-dimensional — has x and y
real signals are analog signals that are continuous in all dimensions
a computer has limited space and can’t process them
therefore, digitise — sampling + quantisation
Sampling
Quantisation
analog to digital converter (ADC) — converts from analog (continuous) to digital (discrete) signal
takes input analog and reference voltage, outputs the fraction of input voltage in reference voltage
digital-to-analog converter — ‘reconstruction’
a discrete signal is represented by a sequence of samples s[n]
s[n] = s(nTs)
the sampling rate must be at least twice the highest frequency
the highest useful frequency from an FFT is half of the sampling frequency
if it’s not obeyed and your sample rate is too low, you get aliasing (false data)