Frequency shifting has been used in public address systems to help control feedback since the 1960’s. Feedback gets generated at portions of the transfer function where the gain is greater than 0 dB.
The loudspeaker to microphone transfer function, when measured in a room, has peaks and valleys in the magnitude response.
In frequency shifting all frequencies of a signal are shifted up or down by some number of hertz. The basic idea behind a frequency shifter is that as feedback gets generated in one area of the response it eventually gets attenuated by another area.
The frequency shifter continues to move the generated feedback frequency along the transfer function until it reaches a section that effectively attenuates the feedback. The effectiveness of the shifter depends in part on the system transfer function.
It is worth pointing out that this is not a “musical transformation” as the ratio between the signal’s harmonics is not preserved by the frequency shift. A person’s voice will begin to sound mechanical as the amount of the shift increases.
While “audible distortion” depends on the experience of the listener most agree that the frequency shift needs to be less than 12 Hz.
How much added gain before feedback can be reasonably expected? The short answer is only a couple of dB. Hansler (1) reviews some research results that indicate that actual increase in gain achieved depends on the reverberation time as well as the size of the frequency shift.
Using frequency shifts in the 6-12 Hz range, a lecture hall with minimal reverberation benefited by slightly less than 2 dB. An echoic chamber with reverberation time of greater than 1 second could benefit by nearly 6 dB by the same frequency shift.
Digital signal processing allows frequency-shifting techniques in a large variety of applications. When used in conjunction with other methods such as the adaptive filter modeling previously mentioned, it can provide an even greater benefit.
However, the artifacts due to the frequency shifting are prohibitive in areas where a pure signal is desired. Musicians are more sensitive to frequency shifts, so think twice before placing a shifter in their monitor loudspeaker path.
Automatic notch filters have been used to control feedback (2) since at least the 1970’s. Digital signal processing allows more flexibility in terms of frequency detection as well as frequency discrimination and the method of deploying notches.
Auto-notching is found more frequently among pro-audio users than the other methods because it is easier to manage the distortion.
When considering automatic notching algorithms there are three areas of focus: frequency identification, feedback discrimination and notch deployment.
Frequency identification typically is accomplished by using either a version of the Fourier transform or an adaptive notch filter. Both methods of detection allow the accurate identification of potential feedback frequencies.
While the Fourier transform is naturally geared toward frequency detection, the adaptive notch filter can also determine frequency by analyzing the coefficient values of the adaptive filter. However, detection of lower frequencies (less than 100 Hz) are problematic for both algorithms.
Fourier analysis requires a longer analysis window to accurately determine lower frequencies and the adaptive notch filter requires greater precision.