What is a key characteristic of filters used in signal processing?

A key characteristic of filters used in signal processing is that they selectively allow certain frequencies to pass while attenuating others. This selectivity is fundamental to the function of filters, as they can be designed to target specific frequency ranges based on application needs, such as removing noise or isolating a particular signal component.

Filters are categorized into various types, such as low-pass, high-pass, band-pass, and band-stop, each of which serves a different purpose in frequency selection. For example, a low-pass filter allows signals with frequencies below a certain cutoff frequency to pass through while attenuating higher frequencies. This makes filters essential tools in applications ranging from audio processing to telecommunications and data analysis.

While it's true that filters cannot completely eliminate all frequencies (as processes may introduce imperfections or limitations), and they do not inherently increase signal power or combine multiple signals in their basic operation, their primary function is centered around frequency selectivity, which is accurately captured by the correct answer.