Question about linear combination of non-stationary signals

1. Which transform is suitable for non-stationary signal?
2. Why is speech a non-stationary signal?
3. What does non-stationary signal mean?
4. How do you know if a signal is stationary?

Which transform is suitable for non-stationary signal?

For signals changing their characteristics over time the method of analysis that presents the signal changes in both time and frequency is required, and one of the most valid methods is wavelet transform.

Why is speech a non-stationary signal?

Speech signal processing deviates in this aspect. This is because, speech is an example for non-stationary signal where as conventional synthetic signals like sine wave, triangular wave, square wave and so on are stationary in nature. Hence different approaches and tools are needed to process the speech signal.

What does non-stationary signal mean?

A stationary time series has statistical properties or moments (e.g., mean and variance) that do not vary in time. Stationarity, then, is the status of a stationary time series. Conversely, nonstationarity is the status of a time series whose statistical properties are changing through time.

How do you know if a signal is stationary?

For a stationary signal, the basic signal properties of mean and variance do not change over time. For such a signal, the measurement of the mean or variance over only one segment is sufficient to estimate the signal's true mean.