create huffman algorithm without using builtin functions in matlab

To create a Huffman algorithm without using built-in functions in MATLAB, you can follow these steps:

1. Calculate the frequency of each character in the input text.

   • Iterate through the input text and count the occurrence of each character.
   • Store the frequencies in a data structure.

2. Create a priority queue (min heap) based on the character frequencies.

   • Implement a min heap data structure to store the characters and their frequencies.
   • The character with the lowest frequency should have the highest priority.

3. Build the Huffman tree using the priority queue.

   • While the priority queue has more than one node:
     • Remove the two nodes with the lowest frequency (highest priority) from the priority queue.
     • Create a new internal node with the sum of their frequencies.
     • Assign the two nodes as the children of this new internal node.
     • Insert the new internal node back into the priority queue.

4. Traverse the Huffman tree to determine the binary codes for each character.

   • Start at the root of the Huffman tree.
   • Traverse the tree recursively, assigning a '0' for each left branch and a '1' for each right branch.
   • Keep track of the binary code for each character in a lookup table.

5. Encode the input text using the generated Huffman codes.

   • Iterate through each character in the input text.
   • Retrieve the corresponding binary code from the lookup table.
   • Concatenate the binary codes to form the encoded text.

Here is an example implementation of the Huffman algorithm in MATLAB:

main.m
function huffmanEncoding(inputText)
    % Step 1: Calculate character frequencies
    frequencies = calculateFrequencies(inputText);

    % Step 2: Create priority queue
    priorityQueue = createPriorityQueue(frequencies);

    % Step 3: Build Huffman tree
    huffmanTree = buildHuffmanTree(priorityQueue);

    % Step 4: Generate Huffman codes
    huffmanCodes = generateHuffmanCodes(huffmanTree);

    % Step 5: Encode input text
    encodedText = encodeText(inputText, huffmanCodes);

    disp(encodedText);
end

function frequencies = calculateFrequencies(inputText)
    % Code to calculate character frequencies
    % ...

    frequencies = yourCalculatedFrequencies;
end

function priorityQueue = createPriorityQueue(frequencies)
    % Code to create priority queue
    % ...

    priorityQueue = yourCreatedPriorityQueue;
end

function huffmanTree = buildHuffmanTree(priorityQueue)
    % Code to build Huffman tree
    % ...

    huffmanTree = yourBuiltHuffmanTree;
end

function huffmanCodes = generateHuffmanCodes(huffmanTree)
    % Code to generate Huffman codes from the tree
    % ...

    huffmanCodes = yourGeneratedHuffmanCodes;
end

function encodedText = encodeText(inputText, huffmanCodes)
    % Code to encode input text using Huffman codes
    % ...

    encodedText = yourEncodedText;
end

% Example usage
inputText = 'Hello, World!';
huffmanEncoding(inputText);
1386 chars
58 lines

Please note that the code provided above is just an outline and you would need to implement the missing parts according to your specific requirements.