In signal processing, sub-band coding (SBC) is any form of transform coding that breaks a signal into a number of different frequency bands, typically by using a fast Fourier transform, and encodes each one independently. This decomposition is often the first step in data compression for audio and video signals. SBC is the core technique used in many popular lossy audio compression algorithms including MP3. The simplest way to digitally encode audio signals is pulse-code modulation (PCM), which is used on audio CDs, DAT recordings, and so on. Digitization transforms continuous signals into discrete ones by sampling a signal's amplitude at uniform intervals and rounding to the nearest value representable with the available number of bits. This process is fundamentally inexact, and involves two errors: discretization error, from sampling at intervals, and quantization error, from rounding. The more bits used to represent each sample, the finer the granularity in the digital representation, and thus the smaller the quantization error. Such quantization errors may be thought of as a type of noise, because they are effectively the difference between the original source and its binary representation. With PCM, the audible effects of these errors can be mitigated with dither and by using enough bits to ensure that the noise is low enough to be masked either by the signal itself or by other sources of noise. A high quality signal is possible, but at the cost of a high bitrate (e.g., over 700 kbit/s for one channel of CD audio). In effect, many bits are wasted in encoding masked portions of the signal because PCM makes no assumptions about how the human ear hears. Coding techniques reduce bitrate by exploiting known characteristics of the auditory system. A classic method is nonlinear PCM, such as the μ-law algorithm. Small signals are digitized with finer granularity than are large ones; the effect is to add noise that is proportional to the signal strength. Sun's for sound is a popular example of mu-law encoding.

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