Redundancy (information theory)

<p>In <a href="/facts/Information_theory/qNLH3U5P">information theory</a>, redundancy measures the fractional difference between the <a href="/facts/Entropy_(information_theory)/NLg4NLvt">entropy</a> H(X) of an ensemble X, and its maximum possible value 
  
    
      
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    {\displaystyle \log(|{\mathcal {A}}_{X}|)}
  
. Informally, it is the amount of wasted "space" used to transmit certain data. <a href="/facts/Data_compression/gMFuY4FT">Data compression</a> is a way to reduce or eliminate unwanted redundancy, while <a href="/facts/Forward_error_correction/cLUTUJrA">forward error correction</a> is a way of adding desired redundancy for purposes of <a href="/facts/Error_detection_and_correction/o2rH8e3n">error detection and correction</a> when communicating over a noisy <a href="/facts/Communication_channel/MtlxEShV">channel</a> of limited <a href="/facts/Channel_capacity/55wJYsS6">capacity</a>.
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Redundancy (information theory) open-in-new

Redundancy (information theory)