Communications Toolbox

Creating a Huffman Code Dictionary

Huffman coding requires statistical information about the source of the data being encoded. In particular, the p input argument in the huffmandict function lists the probability with which the source produces each symbol in its alphabet.

For example, consider a data source that produces 1s with probability 0.1, 2s with probability 0.1, and 3s with probability 0.8. The main computational step in encoding data from this source using a Huffman code is to create a dictionary that associates each data symbol with a codeword. The commands below create such a dictionary and then show the codeword vector associated with a particular value from the data source.

symbols = [1 2 3]; % Data symbols
p = [0.1 0.1 0.8]; % Probability of each data symbol
dict = huffmandict(symbols,p) % Create the dictionary.
dict{1,:} % Show one row of the dictionary.

The output below shows that the most probable data symbol, 3, is associated with a one-digit codeword, while less probable data symbols are associated with two-digit codewords. The output also shows, for example, that a Huffman encoder receiving the data symbol 1 should substitute the sequence 11.

dict = 

    [1]    [1x2 double]
    [2]    [1x2 double]
    [3]    [         0]


ans =

     1


ans =

     1     1

Huffman Coding

Example: Creating and Decoding a Huffman Code

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