FFT filters refer to numerical algorithms based on the FFT or Fast Fourier Transforms policy. The basic target of an FFT filter is to allow the conversion of the time element into a frequency element. Fourier transform filters are also able to do the reverse and allows for the seemingly endless computation of both elements. With this particular function, FFT filters are used by various industries including various fields in mathematics, engineering, and science. The use of FFT filtration or Fast Fourier transformation started only in 1965 with basic algorithm policies. These basic policies eventually led to various more complex algorithms including group theories, complex number arithmetic, and number theories.
The use of FFT filtration is widely used in the music industry. This is especially applicable to musical composers and arrangers that use the help of various computer programs and devices to create variations in terms of notes and musical tones. In the case of musical arrangers for example, FFT filters can serve to help sound equalization. The best thing about applications that use FFT filters is that it features simple dragging of rubber band-like pointers to allow music adjustments and editing. FFT filters also allow increasing window display size of various function tools to ensure accuracy of so-called music filtration.
FFT filtration may also be applied to comparing similar musical pieces in terms of overtones. On standard audio devices, some notes may seem to be very similar but when processed through FFT filters, there are actually different overtones that can help distinguish one from the other. The only problem with handling overtones is that it would take a very long time and a lot of patience to be able to successfully plot them. With the FFT use as a musical tool, handling of musical and note overtones are made easier and much faster resulting to better musical note accuracy and arranging efficiency.