{"id":182767,"date":"2024-03-27T08:06:00","date_gmt":"2024-03-27T07:06:00","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=182767"},"modified":"2024-03-10T21:20:17","modified_gmt":"2024-03-10T20:20:17","slug":"huffman-coding-description-and-instructions-for-use","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/huffman-coding-description-and-instructions-for-use","title":{"rendered":"Huffman coding: Description and instructions for use"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"182767\" class=\"elementor elementor-182767\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d5cc8b7 e-flex e-con-boxed e-con\" data-id=\"d5cc8b7\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9cbf42a elementor-widget elementor-widget-heading\" data-id=\"9cbf42a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Huffman coding is a data compression algorithm. The idea is to assign variable-length codes to the input characters, the length of the assigned codes being based on the frequency of occurrence of the characters in the initial sequence.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f0a86cc elementor-widget elementor-widget-text-editor\" data-id=\"f0a86cc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>Huffman coding<\/strong> is a lossless data compression algorithm. The algorithm was invented in 1952 by David Albert Huffman. <strong>Huffman coding<\/strong> is generally important for compressing data containing frequently occurring characters.<\/p><p>The <strong>frequency factor<\/strong> is taken into account here because of the notion of information entropy, since the more frequent a character is, the higher its entropy.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-52c4ab6 e-flex e-con-boxed e-con\" data-id=\"52c4ab6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c102c90 elementor-widget elementor-widget-heading\" data-id=\"c102c90\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">How does Huffman coding work?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0a6fe61 elementor-widget elementor-widget-text-editor\" data-id=\"0a6fe61\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>The principle of Huffman coding is based on the construction of a tree structure with nodes.<\/p><ul><li>This algorithm is based on the idea that the best way to code information is to find the optimal length to represent each character in the initial sequence.<\/li><li>The optimal length of the code corresponding to a character is given by the number of branches that need to be traversed from the top of the Huffman Tree to arrive at this character, which will always be a leaf of the Huffman Tree.<\/li><\/ul><p>\u00a0<\/p><p>The idea behind the <strong>Huffman Tree<\/strong> is to minimize the length of the symbols used to encode a message, which in a way means minimizing the size of the tree. But how is the Huffman tree constructed?<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ee78104 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"ee78104\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">All about Huffman coding<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-42cd688 e-flex e-con-boxed e-con\" data-id=\"42cd688\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ef0fb16 elementor-widget elementor-widget-heading\" data-id=\"ef0fb16\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is the principle of Huffman coding?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ef547ef elementor-widget elementor-widget-text-editor\" data-id=\"ef547ef\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>As for the <strong>construction of the tree,<\/strong> we associate each time the two nodes with the lowest weights, to give a new &#8220;father&#8221; node whose weight is equivalent to the sum of the weights of its children.<\/p><p>This process is <strong>repeated until only one node remains:<\/strong> the root of the Huffman tree, whose weight is the sum of the weights of all the initial leaf nodes.<\/p><p>We <strong>then associate, for example, code 0 with each left-hand branch<\/strong> and code 1 with each right-hand branch.<\/p><p>To<strong> obtain the binary code of each character<\/strong>, we run through the tree from top to bottom, each time taking the 0 or 1 character of the branches we pass through, depending on whether we&#8217;re going right or left.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0e0d3a6 e-flex e-con-boxed e-con\" data-id=\"0e0d3a6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5f50b10 elementor-widget elementor-widget-heading\" data-id=\"5f50b10\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">The different stages in the construction of the Huffman Tree<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62282b2 elementor-widget elementor-widget-text-editor\" data-id=\"62282b2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ol><li aria-level=\"1\">Construct leaf nodes from each character of the message to be coded, each character being taken into account only once with the different frequencies of appearance of the characters to be arranged in order of priority, the highest priority being those with the lowest frequencies.<\/li><li aria-level=\"1\">Extract the two lowest-weight nodes in ascending order of frequency, i.e. the node with the lowest frequency should be extracted first.<\/li><li aria-level=\"1\">Create a new internal node with a frequency equal to the sum of the frequencies of these two nodes. Define the first node extracted as the left-hand child of this node and the second node as the right-hand child. Add the newly created node to the list of remaining nodes.<\/li><li aria-level=\"1\">Repeat steps 2 and 3 until you have passed through all the nodes obtained in step 1. The remaining node is the root of the tree and construction is complete.<\/li><\/ol>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-df92a2b e-flex e-con-boxed e-con\" data-id=\"df92a2b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3123058 elementor-widget elementor-widget-heading\" data-id=\"3123058\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">An example to illustrate coding<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a79e0d elementor-widget elementor-widget-text-editor\" data-id=\"5a79e0d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>To illustrate the idea of <strong>Huffman coding,<\/strong> we&#8217;ll consider the message below, which we&#8217;ll optimally represent in binary form:<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cf3646 elementor-widget elementor-widget-code-highlight\" data-id=\"5cf3646\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"prismjs-tomorrow  \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-git \">\n\t\t\t\t<code readonly=\"true\" class=\"language-git\">\n\t\t\t\t\t<xmp>aabbccddbbeaebdddfffdbffddabbbbbcdefaabbcccccaabbddfffdcecc<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b6a2b36 elementor-widget elementor-widget-text-editor\" data-id=\"b6a2b36\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>For a message to be coded like this one, let&#8217;s start by counting the frequency of distinct characters in the message. After counting, we obtain the following result:<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-921836f elementor-widget elementor-widget-code-highlight\" data-id=\"921836f\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"prismjs-tomorrow  \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-git \">\n\t\t\t\t<code readonly=\"true\" class=\"language-git\">\n\t\t\t\t\t<xmp>a:8, b:15, c:11, d:12, e:4, f:9<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a1780b0 elementor-widget elementor-widget-text-editor\" data-id=\"a1780b0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>We will implement the Huffman coding algorithm on this example.<\/p><p>The<strong> first step is to use the least frequent characters in the message to be coded.<\/strong> We&#8217;ll start with the letters &#8216;e&#8217; and &#8216;a&#8217;, which have the lowest frequencies, then sum their weights, i.e. their frequencies of appearance, in order to replace the two characters with a new single character whose frequency will be the sum of the frequencies of these two characters in the list. At the end of this first step, the list becomes :<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d50035c elementor-widget elementor-widget-code-highlight\" data-id=\"d50035c\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"prismjs-tomorrow  \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-git \">\n\t\t\t\t<code readonly=\"true\" class=\"language-git\">\n\t\t\t\t\t<xmp>new node:12, b:15, c:11, d:12, f:9<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-29d17cb elementor-widget elementor-widget-text-editor\" data-id=\"29d17cb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<span style=\"font-weight: 400;\">where the <\/span><b>new node<\/b><span style=\"font-weight: 400;\"> replaces nodes a and e with a weight equal to the sum of their respective weights. <\/span><strong>[ new node : 12 = (a:8, e:4)]<\/strong>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff1db40 elementor-widget elementor-widget-text-editor\" data-id=\"ff1db40\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Then, from the new list obtained, choose the two elements with the lowest weights, and iterate the process until you obtain the node with the highest weight, i.e. with the weight of the sum of the frequencies of all the characters. Note that at the end of the Huffman tree construction, all the distinct characters of the initial message to be coded are leaves of the Huffman tree. At the end of the run, we obtain the following results:<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c6e575 elementor-widget elementor-widget-code-highlight\" data-id=\"7c6e575\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"prismjs-tomorrow  \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-git \">\n\t\t\t\t<code readonly=\"true\" class=\"language-git\">\n\t\t\t\t\t<xmp>d -> 00 \r\ne -> 010 \r\na -> 011 \r\nb -> 10 \r\nf -> 110 \r\nc -> 111<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-74f08ef e-flex e-con-boxed e-con\" data-id=\"74f08ef\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-97d3bc8 elementor-widget elementor-widget-text-editor\" data-id=\"97d3bc8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<span style=\"font-weight: 400;\">Remember that the labels of the Huffman tree are marked by taking the convention of putting a 0 on the left label and a 1 on the right label in descending order i.e. from the root of the tree to the leaves.<\/span>\n\n<span style=\"font-weight: 400;\">The time complexity of this algorithm is quasi-linear i.e. in <\/span><em><b>O(nlogn)<\/b><\/em> <span style=\"font-weight: 400;\">where <\/span><em><span style=\"font-weight: 400;\">n <\/span><\/em><span style=\"font-weight: 400;\">is the number of unique characters in the list to be compressed and the space complexity is linear so in<\/span> <b><em>O(n)<\/em>. <\/b>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cb5cc1 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"5cb5cc1\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Mastering Huffman coding<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5174cf3 elementor-widget elementor-widget-shortcode\" data-id=\"5174cf3\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/JosephNg01\/dd35df12fb80660f895287244d4c5ad1.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f12d3f3 e-flex e-con-boxed e-con\" data-id=\"f12d3f3\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a73eb8d elementor-widget elementor-widget-heading\" data-id=\"a73eb8d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is Huffman coding used for in working life?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-46563be elementor-widget elementor-widget-text-editor\" data-id=\"46563be\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>The various applications of the Huffman coding algorithm for data compression include fax and text transmission, conventional compression formats such as GZIP, and multimedia software such as JPEG, PNG and MP3.<\/p><p>In general, data compression is useful for increasing memory storage capacity or data transmission speed.<\/p><p>There are a number of variations on Huffman coding when creating a tree.<\/p><ul><li>Either the dictionary is static: each character has a predefined code that is known or published in advance (and therefore does not need to be transmitted);<\/li><li>or the dictionary is semi-adaptive: the content is analyzed to calculate the frequencies of each character, and an optimized tree is used for coding (it must then be transmitted for decoding);<\/li><li>Or the dictionary is adaptive: starting from a known tree (published beforehand and therefore not transmitted), it is modified during compression and optimized as it goes along. The computation time is much longer, but often offers a better compression ratio.<\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c6d77b elementor-widget elementor-widget-text-editor\" data-id=\"3c6d77b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Ultimately, <strong>Huffman coding<\/strong> is a very useful data compression algorithm with many applications today, from increasing storage capacity to increasing data transmission speed. There are several variants of this data compression technique, including the dynamic variant, which is an improvement on the static variant presented in this article.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5417d25 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"5417d25\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Training in Huffman coding<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9f967f6 e-flex e-con-boxed e-con\" data-id=\"9f967f6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-19b5d67 elementor-widget elementor-widget-html\" data-id=\"19b5d67\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"How does Huffman coding work?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"The principle of Huffman coding is based on the construction of a tree structure with nodes. This algorithm is based on the idea that the best way to encode information is to find the optimal length to represent each character in the initial sequence. The optimal length of the code corresponding to a character is given by the number of branches that must be traversed from the top of the Huffman Tree to reach this character, which will always be a leaf of the Huffman Tree\".\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What is the principle of Huffman coding?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"As far as the tree construction is concerned, each time we associate the two nodes with the lowest weights, to give a new node \"father\" whose weight is equivalent to the sum of the weights of its children. This process is repeated until only one node remains: the root of the Huffman tree, whose weight is the sum of the weights of all the initial leaf nodes.\"\n    }\n  }]\n}\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Huffman coding is a data compression algorithm. The idea is to assign variable-length codes to the input characters, the length of the assigned codes being based on the frequency of occurrence of the characters in the initial sequence. Huffman coding is a lossless data compression algorithm. The algorithm was invented in 1952 by David Albert [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":182770,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Huffman coding: Description and instructions for use<\/title>\n<meta name=\"description\" content=\"Huffman coding provides an efficient way to compress data while preserving its original content, making it a..\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/en\/huffman-coding-description-and-instructions-for-use\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Huffman coding: Description and instructions for use\" \/>\n<meta property=\"og:description\" content=\"Huffman coding is a data compression algorithm. 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