What does suppression refer to in signal processing?

Suppression in signal processing refers to the elimination of undesired portions of a signal, which aligns with the correct answer. This process involves reducing or removing certain frequencies or noise components that do not contribute to the desired information within the signal. By suppressing these unwanted elements, the clarity and quality of the main signal can be significantly improved, allowing for better analysis and interpretation.

In various applications, such as audio processing or communications, suppression is critical for enhancing the intelligibility of the main signal by removing background noise or interference. This ensures that the relevant information can be more easily discerned and processed.

The other options address aspects of signal manipulation that are distinct from suppression. For instance, enhancing the main signal is more about boosting specific characteristics or features within the signal rather than removing unwanted parts. Amplification refers to increasing the strength of weak signals, which does not involve elimination, and broadening signal bandwidth pertains to altering the range of frequencies a signal occupies, which is a different concept altogether.