The error correction code used in digital music systems such as CD players and DVD players.

CD discs typically have a raw error rate of around one in every 0.1 to 1 million bits. In English, it translates into around 0.4 to 4 errors a second. Without any correction codecs, the CD will sound like a squeaky screeching piece of junk, with no better use than as a coaster on your coffee table.

Error correction involves the use of interleaving and concealment to hide errors. Interleaving involves the distribution of data into seperate places, hence a long burst error (a long continued interruption of data) will become many smaller errors, hence much more easily corrected or concealed.

The Reed-Solomon algorithm is a highly efficient error correction code. CD's can actually hold a lot more data than they do, if they did not use parity bits to check for errors. But then again, they would be useless coasters if there was no error correction.

The details of this code are far too complicated to be easily explained here, so in short, it basically involves the use of two polynomial equations to check divided segments of data on the medium (in this case, the CD). If the segment was error free, the answer to both equations would be zero, and the CD moves on. However, if a non-zero result occurs, then by weighing the difference in the answers (because it is a polynomial equation, as far as I understand this algorithm, the higher the power, the higher the non-zero result causing the error, therefore the location of the error can be determined), the error correction system then can use first its error correction code, then if it is not possible to correct the error, then the concealment code to fix the jitter.

All in all, the code is so effective that you can drill a hole an-eighth of an inch into a music CD and you can still play it. Rather amazing.

Phew! Now how is that for trivial knowledge? Bet all that doesn't go through your head when you listen to a music CD on your player. Imagine this scenario:

I will take CD players for $1000

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