[GRC]

Google can be your friend; as can Wikipedia;

"An anti-aliasing filter is a filter used before a signal sampler, to restrict the bandwidth of a signal to approximately satisfy the sampling theorem. Since the theorem states that unambiguous interpretation of the signal from its samples is possible only when the power of frequencies outside the Nyquist bandwidth is zero, the anti-aliasing filter would have to have perfect stop-band rejection to completely satisfy the theorem. Every realizable anti-aliasing filter will permit some aliasing to occur; the amount of aliasing that does occur depends on how good the filter is.

Anti-aliasing filters are commonly used at the input of digital signal processing systems, for example in sound digitization systems; similar filters are used as reconstruction filters at the output of such systems, for example in music players. In the latter case, the filter is to prevent aliasing in the conversion of samples back to a continuous signal, where again perfect stop-band rejection would be required to guarantee zero aliasing.

The theoretical impossibility of realizing perfect filters is not much an impediment in practice, though practical considerations do lead to system design choices such as oversampling to make it easier to realize "good enough" anti-aliasing filters."


Aliasing; also from Wikipedia

"In statistics, signal processing, computer graphics and related disciplines, aliasing refers to an effect that causes different continuous signals to become indistinguishable (or aliases of one another) when sampled. It also refers to the distortion or artifact that results when a signal is sampled and reconstructed as an alias of the original signal.

Temporal aliasing is a major concern in the sampling of video and audio signals. Music, for instance, may contain high-frequency components that are inaudible to us. If we sample it with a frequency that is too low and reconstruct the music with a digital to analog converter, we may hear the low-frequency aliases of the undersampled high frequencies. Therefore, it is common practice to remove the high frequencies with a filter before the sampling is done.

Situations also exist where the low frequencies are removed (if necessary), and the high frequency components are intentionally undersampled and reconstructed as lower ones. Some digital channelizers [1] exploit aliasing in this way for computational efficiency; see IR/RF sampling. Signals that contain no low frequencies are often referred to as bandpass or non-baseband."

So, my take is that the filter will suppress the "distortion or artifact that results when a signal is sampled and reconstructed as an alias of the original signal" - but I can't figure out yet if you want fast, med or accurate.....