What type of analysis is typically performed on signals to identify their frequency components?

Spectral analysis is the process utilized to identify the frequency components of signals. This technique involves transforming a signal from the time domain into the frequency domain, typically using methods such as the Fourier transform. By doing so, it allows for the visualization and examination of the various frequencies present in the signal, revealing important characteristics such as amplitude and phase at each frequency.

This type of analysis is crucial in various fields, including engineering, physics, and medical diagnostics, as it can help identify patterns, noise, and signals of interest within complex waveforms. In contrast, other types of analysis do not focus primarily on frequency components. Time analysis primarily looks at how signals change over time without delving into frequency specifics. Statistical analysis involves applying statistical methods to interpret data, which may not provide the frequency detail needed. Qualitative analysis assesses characteristics that are descriptive rather than numerical, often ignoring the underlying frequency details essential for understanding signal behavior. Thus, the designation of spectral analysis as the correct answer is well-founded, given its specific role in identifying frequency components of signals.