entropykódolási
Entropykódolási refers to a class of data compression techniques that exploit the statistical properties of information sources. The fundamental principle behind entropy coding is that data with predictable patterns can be represented more efficiently than data with random patterns. It aims to assign shorter codes to more frequent symbols and longer codes to less frequent symbols, thereby minimizing the average code length.
The theoretical limit for lossless data compression is dictated by the entropy of the information source, a
Common types of entropy coding algorithms include Huffman coding and arithmetic coding. Huffman coding constructs a
These techniques are widely used in various data compression standards, such as JPEG for images, MP3 for