Build Huffman Tree with Ternary System

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In summary: It is difficult to prove that the algorithm yields optimal ternary codes. However, the Huffman algorithm is known to produce good codes, so it is likely that the algorithm produces optimal codes.
  • #1
evinda
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Hello! (Wave)

Steps to build Huffman Tree
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.


  • 1. Create a leaf node for each unique character and build a min heap of all leaf nodes (Min Heap is used as a priority queue. The value of frequency field is used to compare two nodes in min heap. Initially, the least frequent character is at root)

    2. Extract two nodes with the minimum frequency from the min heap.

    3. Create a new internal node with frequency equal to the sum of the two nodes frequencies. Make the first extracted node as its left child and the other extracted node as its right child. Add this node to the min heap.

    4. Repeat steps#2 and #3 until the heap contains only one node. The remaining node is the root node and the tree is complete.
At a heap, a node can have at most $2$ children, right?So if we would like to generalize the Huffman algorithm for coded words in ternary system (i.e. coded words using the symbols $0$ , $1$ and $2$ ) what could we do? Do we have to create a tree all the nodes of which have $3$ children? (Thinking)
 
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  • #2
I think that it would be as follows.

Steps to build Huffman Tree
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.


  • 1. Create a leaf node for each unique character and build a min heap of all leaf nodes

    2. Extract three nodes with the minimum frequency from the min heap.

    3. Create a new internal node with frequency equal to the sum of the three nodes frequencies. Make the first extracted node as its left child, the second extracted node as its middle child and the third extracted node as its right child. Add this node to the min heap.

    4. Repeat steps#2 and #3 until the heap contains only one node. The remaining node is the root node and the tree is complete.
How can we prove that the algorithm yields optimal ternary codes? (Thinking)
 

1. What is the purpose of building a Huffman Tree using the Ternary System?

The purpose of building a Huffman Tree with the Ternary System is to create an efficient data compression algorithm. This algorithm allows us to reduce the size of data by replacing frequently used symbols with shorter bit sequences, ultimately saving storage space and increasing the speed of data transmission.

2. How does the Ternary System differ from the Binary System in building a Huffman Tree?

The Ternary System uses three symbols (0, 1, and 2) instead of two (0 and 1) in the Binary System. This allows for more efficient encoding of data, as each symbol in the Ternary System can represent three times more information compared to the Binary System.

3. What is the process for building a Huffman Tree with the Ternary System?

The process for building a Huffman Tree with the Ternary System involves several steps. First, we determine the frequency of each symbol in the data. Then, we arrange these symbols in a tree structure, with the most frequent symbols closer to the root. Next, we assign each symbol a ternary code, with the more frequent symbols having shorter codes. Finally, we use this Huffman Tree to encode the data, replacing frequently used symbols with shorter codes.

4. What are the advantages of using the Ternary System in building a Huffman Tree?

The Ternary System offers several advantages in building a Huffman Tree. It allows for more efficient encoding of data, as each symbol can represent three times more information compared to the Binary System. This results in smaller encoded data and faster transmission speeds. Additionally, the Ternary System can handle a wider range of frequencies compared to the Binary System, making it more versatile in data compression.

5. Can the Ternary System be used in other data compression algorithms besides Huffman Coding?

Yes, the Ternary System can be used in other data compression algorithms besides Huffman Coding. For example, it can be used in arithmetic coding, where it allows for more accurate representation of the probabilities of different symbols. It can also be used in Lempel-Ziv-Welch (LZW) coding, where it allows for more efficient encoding of data with repetitive patterns.

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