Stationary signals have a mean and variance that do not change over time. Their frequency components and amplitudes remain constant. Examples include a frictionless pendulum, single frequency sine waves, and white noise. Non-stationary signals have a mean and variance that vary over time, so their amplitudes and frequencies are time-dependent. Examples of non-stationary signals include speech, EEG, ECG, and PPG recordings.

2. Stationary signals
• The signals for which the
mean and variance of the
signals are time invariant are
called stationary signals.
• In general, the frequency
component(s) and
amplitude(s) of the signal
are independent of time.
• Examples: frictionless
pendulum, single frequency
sine wave, white noise.

3. Non stationary signals
• The signals for which
the mean and variance
varies with time are
called non stationary
signals.
• The amplitudes and
frequencies of the
signals are time
dependent quantities.
• Examples: speech signal,
EEG, ECG,PPG signals.

4. Stationary and non stationary signal