Wel come
So far, the only type of frequency analysis discussed has been on a linear frequency scale, i.e., the frequency axis is set out in a linear fashion. This is suitable for frequency analysis with a frequency resolution that is constant throughout the frequency range, commonly called "narrow band" analysis. The FFT analyzer performs this type of analysis. There are several situations where frequency analysis is desired, but narrow band analysis does not present the data in its most useful form. An example of this is acoustic noise analysis where the annoyance value of the noise to a human observer is being studied. The human hearing mechanism is responsive to frequency ratios rather than actual frequencies. The frequency of a sound determines its pitch as perceived by a listener, and a frequency ratio of two is a perceived pitch change of one octave, no matter what the actual frequencies are.
Computer
For instance if a sound of 100 Hz frequency is raised to 200 Hz, its pitch will rise one octave, and a sound of 1000 Hz, when raised to 2000 Hz, will also rise one octave in pitch. This fact is so precisely true over a wide frequency range that it is convenient to define the octave as a frequency ratio of two, even though the octave itself is really a subjective measure of a sound pitch change.
This phenomenon can be summarized by saying that the pitch perception of the ear is proportional to the logarithm of frequency rather than to frequency itself. Therefore, it makes sense to express the frequency axis of acoustic spectra on a log frequency axis, and this is almost universally done. For instance, the frequency response curves that sound equipment manufacturers publish are always plotted in log frequency. Likewise, when frequency analysis of sound is performed, it is very common to use log frequency plots.
