Digital signal processing uses time series analysis to identify a signal from a mixture of noise and signals. Signal processing uses various methods to perform this identification, like smoothing, correlation, convolution, and so on. Time series helps measure deviations from the stationary behaviors of signals. These drifts or deviations are the noise, as follows: