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  2. Memory ordering - Wikipedia

    en.wikipedia.org/wiki/Memory_ordering

    At the machine level, calling a function usually involves setting up a stack frame for the function call, which involves many reads and writes to machine memory. In most compiled languages, the compiler is free to order the function calls f, g, and h as it finds

  3. Variable-length code - Wikipedia

    en.wikipedia.org/wiki/Variable-length_code

    A code is non-singular if each source symbol is mapped to a different non-empty bit string; that is, the mapping from source symbols to bit strings is injective.. For example, the mapping = {,,} is not non-singular because both "a" and "b" map to the same bit string "0"; any extension of this mapping will generate a lossy (non-lossless) coding.

  4. Lempel–Ziv–Welch - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Welch

    Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch.It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978.

  5. Lossless join decomposition - Wikipedia

    en.wikipedia.org/wiki/Lossless_join_decomposition

    In database design, a lossless join decomposition is a decomposition of a relation into relations , such that a natural join of the two smaller relations yields back the original relation. This is central in removing redundancy safely from databases while preserving the original data. [ 1 ]

  6. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    An important caveat about lossy compression (formally transcoding), is that editing lossily compressed files causes digital generation loss from the re-encoding. This can be avoided by only producing lossy files from (lossless) originals and only editing (copies of) original files, such as images in raw image format instead of JPEG. If data ...

  7. Rate–distortion theory - Wikipedia

    en.wikipedia.org/wiki/Rate–distortion_theory

    Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal number of bits per symbol, as measured by the rate R, that should be communicated over a channel, so that the source (input signal) can be approximately reconstructed at the receiver (output signal) without ...

  8. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    In both lossy and lossless compression, information redundancy is reduced, using methods such as coding, quantization, DCT and linear prediction to reduce the amount of information used to represent the uncompressed data. Lossy audio compression algorithms provide higher compression and are used in numerous audio applications including Vorbis ...

  9. Entropy coding - Wikipedia

    en.wikipedia.org/wiki/Entropy_coding

    More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies ⁡ [(())] ⁡ [⁡ (())], where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to ...