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Vector quantization (VQ) is a data compression method.
PPM is a statistical data compression method based on N-order Markov models.
VQ is a data compression method based on the principle of block coding.
Therefore, a data compression method has to be used for the sake of reducing the volume of data.
Therefore, a data compression method is necessary to store and process this information while preserving as much information as possible.
We used the same data mentioned in Section "Efficiency of data retrieval in DCMS" to test the MS data compression method.
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There are two major types of scientific data compression methods: lossless and lossy methods.
So many data compression methods are proposed, but less focus on the lossless compression.
Wavelet based data compression methods have demonstrated superior performance over the conventional interpolative methods.
Open image in new window Fig. 16 Plots showing the compression and decompression speeds of different scientific data compression methods as a function of the compression ratio.
Because of these flaws, the notion of algorithmic complexity is mainly useful for obtaining ultimate lower bounds for data compression methods.
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