DMC - DMC(Dynamic Markov Compression) (Read Sayood,...

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DMC(Dynamic Markov Compression) (Read Sayood, pp.174-176, Bell et. Al., Managing Gigabytes,pp.69-72) ± Uses a finite state model ± Works at the bit level ± Adaptive ± Slow in performance ± Compression ratio comparable to PPM Initial model : A one state fsa with transitions 0/1 and 1/1. In general, the transitions are marked by 0/ p or 1/ q where p and q denote non-zero counts of number of transitions from that state ( not including the next bit) from a given state with input 0 or 1, respectively. The initial count is set to 1 to take care of the “zero frequency” problem. The estimate of probability of a 0 being the next input is p/(p+q ) and 1 being the next state is q/(p+q) . These probability values are used by a background entropy coder( such as an arithmetic coder) to estimate the interval in the cumulative probability space for the next symbol in the input. If the next symbol is zero, it will change then the count to p+1 , make the appropriate state change and continue. Similarly, for a 1 input which will change the value of q to q+1 . Adaptation(Cloning): If a transition to a particular state t from some previous state u is heavy, that is more frequent, in order to capture this skewed context, the state t is cloned. A threshold value of the count value for cloning must be agreed upon by both encoder and the decoder. The cloned state is designated as t’ . This state t’ records independent probabilities for symbols occurring after a transition from state u to state
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This note was uploaded on 06/09/2011 for the course CAP 5015 taught by Professor Mukherjee during the Spring '11 term at University of Central Florida.

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DMC - DMC(Dynamic Markov Compression) (Read Sayood,...

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