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by the nonnegativity of relative entropy and the fact (Kraft inequality) that c 1. Hence, L H with equality if and only if pi = D li (i.e., if and only if logD pi is an integer for all i). De nition A probability distribution is called D-adic if each of the probabilities is equal to D n for some n. Thus, we have equality in the theorem if and only if the distribution of X is D-adic. The preceding proof also indicates a procedure for nding an optimal code: Find the D-adic distribution that is closest (in the relative entropy sense) to the distribution of X. This distribution provides the set of codeword lengths. Construct the code by choosing the rst available node as in the proof of the Kraft inequality. We then have an optimal code for X. However, this procedure is not easy, since the search for the closest D-adic distribution is not obvious. In the next section we give a good suboptimal procedure (Shannon Fano coding). In Section 5.6 we describe a simple procedure (Huffman coding) for actually nding the optimal code. pdf to excel converter in vb.net Using VB.NET convert a PDF to excel and then re... | Adobe ...
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