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Arithmetic coding
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==Benchmarks and other technical characteristics== Every programmatic implementation of arithmetic encoding has a different compression ratio and performance. While compression ratios vary only a little (usually under 1%),<ref>For instance, {{harvtxt|Howard|Vitter|1994}} discuss versions of arithmetic coding based on real-number ranges, integer approximations to those ranges, and an even more restricted type of approximation that they call binary quasi-arithmetic coding. They state that the difference between real and integer versions is negligible, prove that the compression loss for their quasi-arithmetic method can be made arbitrarily small, and bound the compression loss incurred by one of their approximations as less than 0.06%. See: {{citation | last1 = Howard | first1 = Paul G. | last2 = Vitter | first2 = Jeffrey S. | doi = 10.1109/5.286189 | issue = 6 | journal = Proceedings of the IEEE | pages = 857β865 | title = Arithmetic coding for data compression | url = http://home.tiscali.nl/rajduim/Video%20Compression%20Docs/Arithmetic%20Coding%20For%20Data%20Compression%20(2).pdf | volume = 82 | year = 1994 | access-date = 17 October 2013 | archive-url = https://web.archive.org/web/20131018025150/http://home.tiscali.nl/rajduim/Video%20Compression%20Docs/Arithmetic%20Coding%20For%20Data%20Compression%20(2).pdf | archive-date = 18 October 2013 | url-status = dead | hdl = 1808/7229 | hdl-access = free }}.</ref> the code execution time can vary by a factor of 10. Choosing the right encoder from a list of publicly available encoders is not a simple task because performance and compression ratio depend also on the type of data, particularly on the size of the alphabet (number of different symbols). One of two particular encoders may have better performance for small alphabets while the other may show better performance for large alphabets. Most encoders have limitations on the size of the alphabet and many of them are specialized for alphabets of exactly two symbols (0 and 1).
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