Feedback is a common problem in live sound reinforcement systems. It can be prevented or suppressed by a variety of techniques including noise gates, EQing problem frequencies and lowering gain.
Feedback is also a magnitude and phase issue that can cause significant distortion in a music program. To solve this, adaptive filter algorithms add a decorrelation function (such as a frequency shift) to the input signal.
There are a number of different feedback suppression methods that can be used in live sound systems. Some use frequency shifting to introduce a varying shift in the response of the system while others use adaptive filters.
Frequency shifting has the advantage of only achieving a modest gain increase before feedback occurs. However, it can introduce pitch distortion in the music program.
Adaptive filters can also achieve a small gain increase before feedback but converge much slower. This means that fewer reverberation components are suppressed, which may not be ideal in some venues.
Most feedback suppressors have a special mode for live performance that distinguishes between music and feedback. The algorithm uses logic to place a narrow notch filter on the offending feedback tone before it is noticed by the human ear. It is a good emergency backup plan that will help protect the sound system in case of sudden feedback. This is one of the most important features that a feedback suppressor should have in order to keep the quality of your audio at its best.
Detection is the ability to recognize something that is important or valuable. It can be a simple act of following a trail, such as in military reconnaissance, or a more complex process, like the detection of explosives hidden inside luggage.
Feedback suppression can be a frustrating process for non-professional sound engineers, but there is an easy solution that takes the guesswork out of feedback management: Automatic Feedback Suppression (AFS) and Advanced Feedback Suppression(tm) (AFS(r)), available in several dbx products, use sophisticated filters and algorithms to eliminate feedback in seconds.
Auto-notching algorithms monitor incoming audio for signs of feedback and automatically deploy narrow notch filters at each frequency that feeds back, reducing the gain of that frequency. Usually these filters are static (fixed), but many auto-notching systems can also recycle the filter, so that it is deployed at a new frequency if needed. This enables more control than the simple auto-notching algorithm, and can increase the system’s gain before feedback margin by as much as 10 dB.
Suppression is the voluntary process of pushing unwanted anxiety-provoking thoughts, memories, emotions and fantasies out of awareness. It is a form of defense in psychoanalysis.
Suppressed contents do not enter consciousness, and the person’s re-active awareness of them does not interfere with his/her ability to perceive reality in a positive or constructive way (Chawla and Ostafin 2007). A similar coping strategy is experiential avoidance.
Several studies have shown that suppression of thoughts linked to behaviours such as smoking, alcohol and food intake can lead to increases in these behaviours (Erskine and Georgiou 2010; Erskine et al. 2010, etc).
Monitoring is a routinely recurring activity that begins with project planning and continues throughout the implementation process. It provides managers and project team members with continuous feedback on implementation, identifies actual or potential successes and early indications of problems or lack of progress as they arise to facilitate timely adjustments and modifications in implementation strategies as required.
The term monitoring is often used in combination with evaluation, which is a broader term for the processes and activities set up by organizations to gather and use information on outputs, outcomes and impact. Both are necessary management tools to inform decision-making and demonstrate accountability, but they differ in their scope, aims, methods and costs.
Monitoring usually focuses on process, including how many people or entities an activity reached, when and where it occurred and who delivered it. However, it can also track changes in context (situation), including how an activity’s outcomes might be affected by external factors and whether the underlying assumptions are still valid.