ppm - PPM(Prediction by Partial Match) The Huffman and...

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PPM(Prediction by Partial Match) The Huffman and arithmetic coders are sometimes referred to as the entropy coder . These methods normally use an order (0) model. If a good model with low entropy can be built external to the algorithms, these algorithms can generate the binary codes very efficiently. One of the most well known modeler is prediction by partial match” (PPM ) [ClW84; Moff90]. PPM uses a finite context Order ( k ) model where k is the maximum context that is specified ahead of execution of the algorithm. The program maintains all the previous occurrences of context at each level of k in a table or a trie-like data structure with associated probability values for each context. Exclusion Principle : If a context at a lower level is a suffix of a context at a higher level, this context is excluded at the lower level. Escape Character : At each level and for each distinct context at that level (except the level with k = -1), an escape character is defined whose frequency of occurrence is assumed to be equal to the number of distinct characters occurring for a given context encountered in the text so far encoded, at that context level for the purpose of calculating its probability. The escape character is required to handle the situation when the encoder encounters a new context never encountered before at any context level to give the decoder a signal that the context length has to be reduced by 1. Algorithm : During the encoding process, the algorithm estimates the probability of the occurrence of some given next character in the text stream as follows: the algorithm tries to find the current context of maximum length k for this character in the context table or trie. If the context is not found, it passes the probability of the escape character at this level for this context and goes down one level to
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ppm - PPM(Prediction by Partial Match) The Huffman and...

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