Data compression modeling theory

  • What is the theory of compression?

    In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation.
    Any particular compression is either lossy or lossless.
    Lossless compression reduces bits by identifying and eliminating statistical redundancy..

  • What is the theory of compression?

    Shannon formulated the theory of data compression.
    Shannon established that there is a fundamental limit to lossless data compression.
    This limit, called the entropy rate, is denoted by H.
    The exact value of H depends on the information source --- more specifically, the statistical nature of the source..

Shannon formulated the theory of data compression. Shannon established that there is a fundamental limit to lossless data compression. This limit, called the entropy rate, is denoted by H. The exact value of H depends on the information source --- more specifically, the statistical nature of the source.
Shannon formulated the theory of data compression. Shannon established that there is a fundamental limit to lossless data compression. This limit, called the 

What are the different types of data compression models?

Depending on this criterion we can distinguish between static and adaptive models

In the following we will show the most popular models used in connection with the data compression

I

Static Models In the case of a static model we calculate explicitly the probabilities in advance, we fix them, and we supply them for each example

Statistical tool to model changing systems

In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems.
It is assumed that future states depend only on the current state, not on the events that occurred before it.
Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable.
For this reason, in the fields of predictive modelling and probabilistic forecasting, it is desirable for a given model to exhibit the Markov property.

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