Inelectronics andsignal processing,full scale represents the maximumamplitude a system can represent.
Indigital systems, a signal is said to be atdigital full scale when its magnitude has reached the maximum representable value. Once a signal has reached digital full scale, allheadroom has been utilized, and any further increase in amplitude will result in an error known asclipping. The amplitude of a digital signal can be represented in percent; full scale; ordecibels, full scale (dBFS).
In analog systems, full scale may be defined by the maximum voltage available, or the maximum deflection (full scale deflection orFSD) or indication of an analog instrument such as a moving coil meter orgalvanometer.
Sincebinary integer representation range is asymmetrical, full scale is defined using the maximum positive value that can be represented.[1][2] For example,16-bit PCM audio is centered on the value 0, and can contain values from −32,768 to +32,767. A signal is at full-scale if it reaches from −32,767 to +32,767. (This means that −32,768, the lowest possible value, slightlyexceeds full-scale.)
Signal processing indigital audio workstations often usesfloating-point arithmetic, which can include values past full-scale, to avoid clipping in intermediate processing stages. In afloating-point representation, a full-scale signal is typically defined to reach from −1.0 to +1.0.[3][4]
The signal passes through ananti-aliasing,resampling, orreconstruction filter, which may increase peak amplitude slightly due toringing.
It is possible for theanalog signalrepresented by the digital data to exceed digital full scale even if the digital data does not, and vice versa. Converting to the analog domain, there is no clipping problem as long as the analog circuitry in thedigital-to-analog converter is well designed.
If a full-scale analog signal is converted to digital with sufficient sampling frequency, and thenreconstructed, theNyquist theorem guarantees that there will be no problem in the analog domain due to "peak" issues because the restored analog signal will be an exact copy of the original analog signal. (However, if the signal isnormalized in the digital domain, it may contain "intersample peaks" which exceed full scale after analog reconstruction.)[5]
amplitude of a 997-Hz sine wave whose positive peak value reaches the positive digital full scale, leaving the negative maximum code unused. NOTE In 2's-complement representation, the negative peak is 1 LSB away from the negative maximum code.
amplitude of a 997 Hz sinusoid whose peak positive sample just reaches positive digital full-scale (in 2's-complement a binary value of 0111…1111 to make up the word length) and whose peak negative sample just reaches a value one away from negative digital full-scale (1000…0001 to make up the word length) leaving the maximum negative code (1000…0000) unused
For float data, full scale is 1.
32-bit 0.24 normalized float (type 3 – 32-bit) is the standard floating point format for type 3 .wav files. Values are normalized to the range +/-1.0