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adaptive compression method

Adaptive compression methods adapt data model used during compression in accordance to the compressed data. The compressed message has not to contain the data model. The decoder creates the same model as the coder. The coder compresses the next source unit first and then adapt the model in accordance to this unit. This order enables decoder to create identical model. If the coder changes the model before it compresses the unit, decoder cannot decompress the message because the next unit is compressed using unknown data model. Many of commonly used compression methods are adaptive.

Examples of adaptive compression methods:

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asymetric compression method

Asymetric compression methods have different difficulty of compression and decompression, different time complexity (sometimes memory complexity). The methods use different algorithms for compression and decompression as consequence of previous.

Examples of asymetric compression methods:

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context compression method

Context compression methods use the information about context of input unit during compression. The result of compression is dependent on ambient units.

Example of context compression methods:

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dictionary compression method

Dictionary compression methods use dictinary of phrases during the compression. The dictionary is initialized at the begining. During the compression and decompression the new phrases are added into the dictionary. Dictionary compression methods are adaptive compression methods. The compressed message contains indices of the phrases in the dictionary.

Examples of dictionary compression methods:

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one-pass compression method

One pass compression methods compress data only in one pass. All adaptive compression methods are one pass methods.

Examples of one pass compression methods:

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semi-adaptive compression method

Semi-adaptive compression methods adapt data model in accordance to input data. The compressed message must cantain the data model. The decoder restores the model first and then decompresses the data using this model. Semi-adaptive methods are mostly two pass compression methods - the first pass is used to create the data model.

Examples of semi-adaptive compression methods:

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static compression method

Static compression methods use during compression static data model. The model does not adapt in accordance to the input data. In practice the static data model consists of the frequencies of occurrence of input unit. These frequencies are counted using common rules and then used for compression of all data. The static data model is not compressed with the data. The coder and decoder use the same static model known before compression.

Examples of static compression methods:

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statistic compression method

Statistic compression methods use frequencies of occurrence of units in input data. Usually statistic compression method is two pass compression method too. The first pass is used to count these frequencies.

Examples of statistic compression methods:

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symetric compression method

Symetric compression methods have the same difficulty of compression and decompression, the same time coplexity. The methods use different algorithms for compression and decompression.

Examples of symetric compression methods:

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two-pass compression method

Two pass compression methods need two passes to compress the input text. The first pass is usually used to count frequencies of occurrence of the input units in the data. In the second pass the data are compressed using information from the first pass. Semi-adaptive methods are usually two pass compression methods.

Examples of two pass compression methods:

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