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A low-pass filter preferentially transmits low frequencies and attenuates higher frequencies. It can smooth rapid noise in a slowly varying signal, but it also suppresses wanted variations outside the useful signal bandwidth. An RC low-pass filter gives a concrete continuous-time example; a moving average implements related smoothing on a discrete-time signal.

The useful question is how much change the measurement can tolerate. Preserving the low frequencies of a temperature record while reducing a fast unwanted oscillation can improve readability. Preserving the sharp onset of a pulse requires higher frequencies, so excessive smoothing changes its timing and shape. The RC low-pass frequency response and RC low-pass step response make this signal bandwidth versus settling time tradeoff quantitative.

A signal is a function or sequence representing a quantity that carries information. An electric potential difference measured over time can be written $x(t)$; regularly recorded values give a discrete-time signal $x[n]$. The meaning includes the measured quantity, units, time reference and sampling interval. The same list of numbers sampled once per second or once per millisecond describes different physical frequencies.