How Computer systems Compress Text: Huffman Coding and Huffman Trees



Pcs retail store text (or at the very least English textual content) as eight bits per character. There are a lot of more efficient methods that could operate: so why not use them? And how can we match far more text in considerably less space? Let’s chat about Huffman Coding, Huffman Trees, and Will Smith. Many thanks to the Cambridge Centre for Computing History: Many thanks to Chris Hanel from Aid Class for the graphics: Filmed by Tomek: And many thanks to my proofreading workforce! I am on Twitter on Facebook on and on Snapchat and Instagram as tomscottgo.

About Cryptoplatforming.com

Cryptoplatforming.com is a news websites which gets news around the globe on investing in Crypto. Our news has no backgroundcheck.

22 thoughts on “How Computer systems Compress Text: Huffman Coding and Huffman Trees”

  1. This is the last of the three trial Basics videos! This pushed my quick-explanation skills to the limit, but I figure that "slow down the video and replay if necessary" is better than "let people get bored"…

    Reply
  2. This video was SUPER helpful! Thank you Tom!! I can't go to IRL classes right now – pandemic and all that – and this introductory video is the next best thing. And dare I say, my teachers are not as skilled at succinct explanations. Thanks!!

    Reply
  3. Tom, what would be the consequences if you told your computer to pretend that your compressed file is NOT compressed, and then take every sequence of 8 digits and convert that back into the ASCII letter/digit/symbol? It will be gibberish, but what if you were to make THAT into a Huffman-compressed string? Is there a mathematical proof that says that it will NOT result in any further compression or byte-savings?

    Reply

Leave a Comment